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Автор: Grafiati
Опубліковано: 18 травня 2024

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Статті в журналах з теми "Prediction Of Malignant"

1

Sukanya L. "Risk of malignancy index (RMI) for prediction of malignancy in women with adnexal masses." International Journal of Research in Pharmaceutical Sciences 13, no. 3 (September 26, 2022): 339–42. http://dx.doi.org/10.26452/ijrps.v13i3.2733.

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Ovarian cancer is predominantly cancer in the perimenopausal and post- menopausal age group. A definitive biomarker has not been identified for malignant ovarian cancer and histopathology remains the diagnostic gold standard for this. Risk of Malignancy Index (RMI) in predicting malignant pelvic masses includes serum CA125 level, menopausal status, and ultrasonographic findings. The risk of malignancy index (RMI) was evaluated in the women presented with adnexal masses for its accuracy in predicting the malignancy. This was a retrospective study which included 120 women who presented with adnexal mass in a tertiary hospital. RMI scoring was done based on CA125 levels, ultrasound findings and postmenopausal status and RMI was correlated with the histopathological findings. Out of 120 subjects, 74.1% of subjects were proved to have malignant tumors. RMI in predicting malignancy showed a sensitivity of 88.76%, a specificity of 45.37%, a positive predictive value of 81.63%, a negative predictive value of 66.67% and an accuracy of RMI found to be 82.5%. The RMI is found to be a simple, cost-effective and reliable tool in predicting malignancy in women presenting with adnexal masses that helps in timely referral to a gynaecological oncology center for better management and survival. RMI scoring can be used as it is a better tool for analysing multiple parameters of the tumour.
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2

Wang, Xiuchao, Junjin Wang, Xi Wei, Lihui Zhao, Bo Ni, Zekun Li, Chuntao Gao, et al. "Preoperative ultrasound combined with routine blood tests in predicting the malignant risk of pancreatic cystic neoplasms." Cancer Biology & Medicine 19, no. 10 (November 1, 2022): 1503–16. http://dx.doi.org/10.20892/j.issn.2095-3941.2022.0258.

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Objective: Accurate preoperative identification of benign or malignant pancreatic cystic neoplasms (PCN) may help clinicians make better intervention choices and will be essential for individualized treatment. Methods: Preoperative ultrasound and laboratory examination findings, and demographic characteristics were collected from patients. Multiple logistic regression was used to identify independent risk factors associated with malignant PCN, which were then included in the nomogram and validated with an external cohort. The Net Reclassification Index (NRI) and Integrated Discrimination Improvement (IDI) were calculated to evaluate the improvement in the predictive power of the new model with respect to that of a combined imaging and tumor marker prediction model. Results: Malignant PCN were found in 83 (40.7%) and 33 (38.7%) of the model and validation cohorts, respectively. Multivariate analysis identified age, tumor location, imaging of tumor boundary, blood type, mean hemoglobin concentration, neutrophil-to-lymphocyte ratio, carbohydrate antigen 19-9, and carcinoembryonic antigen as independent risk factors for malignant PCN. The calibration curve indicated that the predictions based on the nomogram were in excellent agreement with the actual observations. A nomogram score cutoff of 192.5 classified patients as having low vs. high risk of malignant PCN. The model achieved good C-statistics of 0.929 (95% CI 0.890–0.968, P < 0.05) and 0.951 (95% CI 0.903–0.998, P < 0.05) in predicting malignancy in the development and validation cohorts, respectively. NRI = 0.268; IDI = 0.271 (P < 0.001 for improvement). The DCA curve indicated that our model yielded greater clinical benefits than the comparator model. Conclusions: The nomogram showed excellent performance in predicting malignant PCN and may help surgeons select patients for detailed examination and surgery. The nomogram is freely available at https://wangjunjinnomogram.shinyapps.io/DynNomapp/.
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3

Li, Tingting, Yanjie Li, Yingqi Yang, Juan Li, ZiYue Hu, Lu Wang, Wei Pu, Ting Wei, and Man Lu. "Logistic regression analysis of ultrasound findings in predicting the malignant and benign phyllodes tumor of breast." PLOS ONE 17, no. 3 (March 24, 2022): e0265952. http://dx.doi.org/10.1371/journal.pone.0265952.

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Objective To evaluate ultrasound characteristics in the prediction of malignant and benign phyllodes tumor of the breast (PTB) by using Logistic regression analysis. Methods 79 lesions diagnosed as PTB by pathology were analyzed retrospectively. The ultrasound features of PTB were recorded and compared between benign and malignant tumors by using single factor and multiple stepwise Logistic regression analysis. Moreover, the Logistic regression model for malignancy prediction was also established. Results There were 79 patients with PTB, including 39 benign PTBs and 40 malignant PTBs (33 borderline PTBs and 7 malignant PTBs by pathologic classification). The area under the ROC curve (AUC) of lesion size and age were 0.737 and 0.850 respectively. There were significant differences in age, lesion size, shape, internal echo, liquefaction, and blood flow between malignant and benign PTBs by using single-factor analysis (P<0.05). Age, internal echo, and liquefaction were significant features by using Logistic regression analysis. The corresponding regression equation In (p/(1 − p) = -3.676+2.919 internal echo +3.029 liquefaction +4.346 age). Conclusion Internal echo, age, and liquefaction are independent ultrasound characteristics in predicting the malignancy of PTBs.
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4

Swan, Kristine Zøylner, Steen Joop Bonnema, Marie Louise Jespersen, and Viveque Egsgaard Nielsen. "Reappraisal of shear wave elastography as a diagnostic tool for identifying thyroid carcinoma." Endocrine Connections 8, no. 8 (August 2019): 1195–205. http://dx.doi.org/10.1530/ec-19-0324.

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Thyroid nodular disease is common, but predicting the risk of malignancy can be difficult. In this prospective study, we aimed to assess the diagnostic accuracy of shear wave elastography (SWE) in predicting thyroid malignancy. Patients with thyroid nodules were enrolled from a surgical tertiary unit. Elasticity index (EI) measured by SWE was registered for seven EI outcomes assessing nodular stiffness and heterogeneity. The diagnosis was determined histologically. In total, 329 patients (mean age: 55 ± 13 years) with 413 thyroid nodules (mean size: 32 ± 13 mm, 88 malignant) were enrolled. Values of SWE region of interest (ROI) for malignant and benign nodules were highly overlapping (ranges for SWE-ROImean: malignant 3–100 kPa; benign 4–182 kPa), and no difference between malignant and benign nodules was found for any other EI outcome investigated (P = 0.13–0.96). There was no association between EI and the histological diagnosis by receiver operating characteristics analysis (area under the curve: 0.51–0.56). Consequently, defining a cut-off point of EI for the prediction of malignancy was not clinically meaningful. Testing our data on previously proposed cut-off points revealed a low accuracy of SWE (56–80%). By regression analysis, factors affecting EI included nodule size >30 mm, heterogeneous echogenicity, micro- or macrocalcifications and solitary nodule. In conclusion, EI, measured by SWE, showed huge overlap between malignant and benign nodules, and low diagnostic accuracy in the prediction of thyroid malignancy. Our study supports that firmness of thyroid nodules, as assessed by SWE, should not be a key feature in the evaluation of such lesions.
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Carlsson, Leo S., Mikael Vejdemo-Johansson, Gunnar Carlsson, and Pär G. Jönsson. "Fibers of Failure: Classifying Errors in Predictive Processes." Algorithms 13, no. 6 (June 23, 2020): 150. http://dx.doi.org/10.3390/a13060150.

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Predictive models are used in many different fields of science and engineering and are always prone to make faulty predictions. These faulty predictions can be more or less malignant depending on the model application. We describe fibers of failure (FiFa), a method to classify failure modes of predictive processes. Our method uses Mapper, an algorithm from topological data analysis (TDA), to build a graphical model of input data stratified by prediction errors. We demonstrate two ways to use the failure mode groupings: either to produce a correction layer that adjusts predictions by similarity to the failure modes; or to inspect members of the failure modes to illustrate and investigate what characterizes each failure mode. We demonstrate FiFa on two scenarios: a convolutional neural network (CNN) predicting MNIST images with added noise, and an artificial neural network (ANN) predicting the electrical energy consumption of an electric arc furnace (EAF). The correction layer on the CNN model improved its prediction accuracy significantly while the inspection of failure modes for the EAF model provided guiding insights into the domain-specific reasons behind several high-error regions.
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Kaseb, Hatem, Ahmad Charifa, Rita Abi-Raad, Guoping Cai, Lynwood Hammers, Manju Prasad, and Adebowale Adeniran. "Concordance Between the TIRADS Ultrasound Scoring Criteria, Fine-Needle Aspiration Cytology, and Thyroid Final Resection Diagnosis." American Journal of Clinical Pathology 152, Supplement_1 (September 11, 2019): S92. http://dx.doi.org/10.1093/ajcp/aqz118.001.

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Abstract Objectives Thyroid imaging reporting and data system (TIRADS) criteria were recently introduced in our institution to aid in predicting diagnosis for various thyroid lesions. We evaluated the association of TIRADS imaging score and fine-needle aspiration (FNA) cytology with thyroid lesions that had a confirmed diagnosis at resection, with a focus on understanding the predictability of this diagnostic tool in malignancy prediction. Methods We assessed the concordance of TIRADS criteria and FNA diagnosis to the final anatomical diagnosis in the assessment of thyroid lesions. We retrieved the cases from the archives of the Yale pathology department between June 2017 and January 2018. Our inclusion criteria included patients who had a TIRADS score, cytology diagnosis, and final surgical resection diagnosis. A total of 65 subjects with an age range of 11 to 88 years were identified. Results The majority of the patients were females, 65% (42/65). Cases with TIRADS score 1-2 (likely benign) and Bethesda I/II nondiagnostic/benign were few since most of these cases did not go for surgical resection. The mildly suspicious TIRAD score 3 and FLUS category showed similar trends, 68% and 67%, respectively, in predicting malignant lesions. The TIRADS score 4 when compared to cytology (IV)/(V) demonstrated similar consistent results in malignancy prediction, both being high at 89% and 87%, respectively. The TIRADS score 5 demonstrated a 95% malignancy prediction. The overall sensitivity and specificity of TIRADS score in our cohort were 66% and 77%, respectively. The positive and negative predictive values of TIRADS score in our cohort were 89% and 39%, respectively. In comparison, the overall sensitivity and specificity of cytology assessment in our cohort were 91% and 44%, respectively. The positive and negative predictive values of cytology assessment in our cohort were 85% and 57%, respectively. Conclusion Our results demonstrated that both cytology and TIRAD score had similar trends in malignancy prediction. Cytological assessment had higher sensitivity but lower specificity compared to TIRADS score. While both techniques showed concordant high predictability of malignant lesions (approximately 91%), the use of both modalities adjunctively will be very useful in triaging cases for surgery. Overall, utilizing TIRADS score with cytology will help reduce the risk of unnecessary invasive procedures in patients with a low probability of malignant thyroid disease.
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Carter, J. R., J. M. Fowler, J. W. Carlson, L. F. Carson, L. L. Adcock, and L. B. Twiggs. "Prediction of malignancy using transvaginal color flow Doppler in patients with gynecologic tumors." International Journal of Gynecologic Cancer 3, no. 5 (1993): 279–84. http://dx.doi.org/10.1046/j.1525-1438.1993.03050279.x.

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Eighty-five patients referred to the Women's Cancer Center, University of Minnesota had transvaginal color flow Doppler performed to determine if pelvic malignancy could be predicted by blood flow assessment. Their mean age was 49 years (range 21–86 years). Thirty-five patients were subsequently found to have malignant tumors of the cervix, uterus or ovary. The presence of increased intratumoral blood flow as depicted by color flow Doppler had a sensitivity of 83%, specificity of 100%, positive predictive value (PPV) of 100% and negative predictive value (NPV) of 89% for malignancy. The mean intratumoral Pulsatility Index (PI) of the patients with malignant tumors was 0.81 (SD 0.24; range 0.3–1.2), which was significantly lower than for the benign group (P= 0.001). A PI of ≤ 1.0 had a sensitivity of 96.3%, specificity of 94.3%, PPV of 89.7% and NPV of 98% for predicting malignancy. Transvaginal color flow Doppler shows promise as a method of predicting malignancy in patients with gynecologic pathology.
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Ohno, Riki, Ryuichi Kawamoto, Mami Kanamoto, Jota Watanabe, Masahiko Fujii, Hiromi Ohtani, Masamitsu Harada, Teru Kumagi, and Hideki Kawasaki. "Neutrophil to Lymphocyte Ratio is a Predictive Factor of Malignant Potential for Intraductal Papillary Mucinous Neoplasms of the pancreas." Biomarker Insights 14 (January 2019): 117727191985150. http://dx.doi.org/10.1177/1177271919851505.

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Intraductal papillary mucinous neoplasms (IPMNs) are cystic neoplasms with the potential for progression to pancreatic cancer. Accurate prediction of the malignant potential is challenging and a proper treatment strategy has not been well established. Preoperative neutrophil-to-lymphocyte ratio (NLR) is a biomarker of the malignant potential in patients with several types of malignancy. We explored malignant potential in patients with IPMN. The present study included 56 patients aged of 73 ± 9 years (mean ± standard deviation) who underwent curative resection for IPMN from 1996 to 2017. We analyzed the relationship between the characteristics including NLR and malignant component for predicting pathological results. The nonmalignant IPMN group (N = 21) included patients with low-grade dysplasia (LGD) and intermediate-grade dysplasia (IGD), and the malignant IPMN group (N = 35) included patients with high-grade dysplasia (HGD) and invasive carcinoma. In a univariate analysis, NLR ⩾ 2.2 ( P = .001), prognostic nutritional index (PNI) < 45 ( P = .016), CA 19-9 > 37 U/mL ( P = .039), and cystic diameter ⩾ 30 mm ( P = .010), and mural nodule ( P = .010) were significantly different between the malignant IPMN and the nonmalignant IPMN groups. Multivariate analysis showed that high NLR (⩾2.2) (odds ratio 9.79; 95% confidence interval: 2.06-45.6), cystic diameter ⩾ 30 mm (4.65; 1.14-18.9), and mural nodule (4.91; 1.20-20.1) were independently predictive of malignant IPMN. These results suggest that preoperative NLR is a useful predictive biomarker for evaluating malignant potential in patients with IPMN.1
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Yamanaka, Shoichiro, Naoki Kawahara, Ryuji Kawaguchi, Keita Waki, Tomoka Maehana, Yosuke Fukui, Ryuta Miyake, Yuki Yamada, Hiroshi Kobayashi, and Fuminori Kimura. "The Comparison of Three Predictive Indexes to Discriminate Malignant Ovarian Tumors from Benign Ovarian Endometrioma: The Characteristics and Efficacy." Diagnostics 12, no. 5 (May 12, 2022): 1212. http://dx.doi.org/10.3390/diagnostics12051212.

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This study aimed to evaluate the prediction efficacy of malignant transformation of ovarian endometrioma (OE) using the Copenhagen Index (CPH-I), the risk of ovarian malignancy algorithm (ROMA), and the R2 predictive index. This retrospective study was conducted at the Department of Gynecology, Nara Medical University Hospital, from January 2008 to July 2021. A total of 171 patients were included in the study. In the current study, cases were divided into three cohorts: pre-menopausal, post-menopausal, and a combined cohort. Patients with benign ovarian tumor mainly received laparoscopic surgery, and patients with suspected malignant tumors underwent laparotomy. Information from a review chart of the patients’ medical records was collected. In the combined cohort, a multivariate analysis confirmed that the ROMA index, the R2 predictive index, and tumor laterality were extracted as independent factors for predicting malignant tumors (hazard ratio (HR): 222.14, 95% confidence interval (CI): 22.27–2215.50, p < 0.001; HR: 9.80, 95% CI: 2.90–33.13, p < 0.001; HR: 0.15, 95% CI: 0.03–0.75, p = 0.021, respectively). In the pre-menopausal cohort, a multivariate analysis confirmed that the CPH index and the R2 predictive index were extracted as independent factors for predicting malignant tumors (HR: 6.45, 95% CI: 1.47–28.22, p = 0.013; HR: 31.19, 95% CI: 8.48–114.74, p < 0.001, respectively). Moreover, the R2 predictive index was only extracted as an independent factor for predicting borderline tumors (HR: 45.00, 95% CI: 7.43–272.52, p < 0.001) in the combined cohort. In pre-menopausal cases or borderline cases, the R2 predictive index is useful; while, in post-menopausal cases, the ROMA index is better than the other indexes.
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Assegie, Tsehay Admassu, R. Lakshmi Tulasi, and N. Komal Kumar. "Breast cancer prediction model with decision tree and adaptive boosting." IAES International Journal of Artificial Intelligence (IJ-AI) 10, no. 1 (March 1, 2021): 184. http://dx.doi.org/10.11591/ijai.v10.i1.pp184-190.

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In this study, breast cancer prediction model is proposed with decision tree and adaptive boosting (Adboost). Furthermore, an extensive experimental evaluation of the predictive performance of the proposed model is conducted. The study is conducted on breast cancer dataset collected form the kaggle data repository. The dataset consists of 569 observations of which the 212 or 37.25% are benign or breast cancer negative and 62.74% are malignant or breast cancer positive. The class distribution shows that, the dataset is highly imbalanced and a learning algorithm such as decision tree is biased to the benign observation and results in poor performance on predicting the malignant observation. To improve the performance of the decision tree on the malignant observation, boosting algorithm namely, the adaptive boosting is employed. Finally, the predictive performance of the decision tree and adaptive boosting is analyzed. The analysis on predictive performance of the model on the kaggle breast cancer data repository shows that, adaptive boosting has 92.53% accuracy and the accuracy of decision tree is 88.80%, Overall, the adaboost algorithm performed better than decision tree.
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Дисертації з теми "Prediction Of Malignant"

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Moitra, Dipanjan. "Deep learning model for prediction of malignant tumors in human body with special reference to multimodel imaging techniques." Thesis, University of North Bengal, 2020. http://ir.nbu.ac.in/handle/123456789/4347.

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Diajil, Ameena Ryhan. "An investigation into the diagnosis, prediction and management of oral potentially malignant disorders." Thesis, University of Newcastle upon Tyne, 2012. http://hdl.handle.net/10443/1601.

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Oral cancer may be proceeded by dysplastic PMDs mainly presenting as leukoplakia or erythroplakia and which can carry an increased risk of malignant transformation. Therefore, early recognition of PMDs with a high potential for cancer development is important to improve patient outcome. 100 patients with dysplastic PMDs presenting in Newcastle underwent a standardised interventional management protocol based on risk factor assessment, laser excision of dysplastic lesions and long-term clinical follow-up at regular intervals. This patient cohort was studied in detail to examine the clinicopathological features that may influence disease progression. Single dysplastic PMDs were mainly observed in the floor of mouth, with 92% presenting as leukoplakia and 8% as erythroplakia. Follow-up revealed that 62% of patients remained disease-free following laser surgery, 17% showed recurrent-disease, 14% new-site dysplasia, with 5% malignant transformation and 2% developed OSCC at a site distant from the primary dysplasia. Clinical appearance, high grade dysplasia, larger sized PMDs, high risk sites and positive excision margins were shown to increase the risk of unfavourable clinical outcome. Malignant transformation was mainly seen in non-smokers and non-alcohol users, whilst new-site OSCC was only seen in non-smokers and light drinkers. The use of Raman spectroscopy in the detection and classification of dysplasia within the human oral tissue was investigated. Currently, histopathology is considered the diagnostic gold standard. Consensus opinion on dysplasia grading of individual PMD lesions using two classification systems (WHO and binary grading) was obtained and a spectral diagnostic model then correlated with the results. The ability of Raman spectroscopy to differentiate between dysplasia and morphologically normal tissue was shown, with an 81% sensitivity and specificity. This supports the suitability of the Raman system in clinical use to distinguish morphologically normal from dysplastic tissue. This work has also shown the efficacy of Raman spectroscopy in identifying early biochemical changes in epithelial dysplastic tissue before morphological/histological change becomes apparent.
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Schiza, Aglaia. "Experimental treatment of patients with disseminated malignant melanoma." Doctoral thesis, Uppsala universitet, Experimentell och klinisk onkologi, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-330710.

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Malignant melanoma (MM) is the deadliest skin cancer with an ever-increasing incidence. New treatments have improved the prognosis for patients with advanced MM. Still, most patients do not respond, and the side effects can be severe, underlining the need for better therapies. The overall aim of this thesis was to evaluate new means to improve the treatment for patients with advanced MM. Immunostimulatory gene therapy (AdCD40L) was evaluated in a clinical study and BRAF-inhibitory treatment in rare cases of BRAF-mutated MM. Due to its immunogenicity, MM is an attractive target for immunostimulatory gene therapy. AdCD40L is an adenovirus carrying the human gene for CD40 ligand, which in different ways can stimulate the immune system to combat cancer. We conducted a Phase I/IIa study with AdCD40L in patients with metastatic MM having received established treatments. In cohort 1 (n=6), four weekly, intratumoural AdCD40L injections were given. In cohort 2 (n=9), low dose cyclophosphamide was added to increase the immune response. Since irradiation may act synergistically with immunotherapy, patients in cohort 3 (n=9) also received a single fraction of radiotherapy (8 Gy). This fraction was given towards the lesion selected for injections. The primary objectives were to assess the feasibility and safety of AdCD40L-treatment and secondarily its anti-tumour effects. Patients were thoroughly assessed for toxicity. The anti-tumour response was evaluated by imaging techniques (FDG-PET/CT, DW-MRI scans), tumour biopsies and blood tests. Plasma protein markers were measured with a multiplex platform. Another objective was to evaluate the potential of DW-MRI and FDG-PET/CT for prediction of AdCD40L treatment response, in terms of overall survival (OS). AdCD40L was well tolerated with mild transient reactions. Local and distant responses in PET/CT scans along with a significantly better 6-month survival in the cohorts that received cyclophosphamide conditioning were observed. Effector lymphocyte responses were elicited. All patients had an increased T effector/T regulatory-cell ratio and death receptors were significantly up-regulated post therapy. Inflammatory cytokines and other plasma proteins were altered in favourable ways by the AdCD40L treatment. The analyses support that the functional DWI parameters may be better early predictors of OS than the established metabolic and morphologic criteria of FDG-PET/CT and CT/MRI, respectively. In conclusion, the stimulation of the CD40 pathway to initiate anti-tumour immunity is a promising treatment alternative for MM patients. However, further studies with developed treatment schemes are warranted. In the first report ever on treatment of a pregnant patient with a BRAF-inhibitor, the therapy was initiated in the second trimester. The treatment with vemurafenib enabled prolonged gestation, hence reducing the risk of immaturity-related complications. Further, we report the first case worldwide of a patient with metastatic conjunctival melanoma who benefitted from treatment with vemurafenib. Additional studies are needed to assess the efficacy of BRAF -inhibitors in the different subtypes of ocular melanoma.
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4

Moitra, Dipanjan. "Deep learning model for prediction of malignant tumors in human body with special reference to multimodel imaging techniques." Thesis, University of North Bengal, 2020. http://ir.nbu.ac.in/handle/123456789/4375.

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Ghosh, Michael [Verfasser]. "Advancing immunopeptidomics : validation of the method, improved epitope prediction, peptide-based HLA typing and discrimination of healthy and malignant tissue / Michael Ghosh." Tübingen : Universitätsbibliothek Tübingen, 2020. http://d-nb.info/1218073012/34.

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Küffer, Stefan Thomas [Verfasser], and Alexander [Akademischer Betreuer] Marx. "IGF1R and TYRO3 as potential biomarkers for response prediction in malignant thymomas and thymic carcinomas treated with sunitinib / Stefan Thomas Küffer ; Betreuer: Alexander Marx." Heidelberg : Universitätsbibliothek Heidelberg, 2019. http://d-nb.info/120260806X/34.

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Küffer, Stefan [Verfasser], and Alexander [Akademischer Betreuer] Marx. "IGF1R and TYRO3 as potential biomarkers for response prediction in malignant thymomas and thymic carcinomas treated with sunitinib / Stefan Thomas Küffer ; Betreuer: Alexander Marx." Heidelberg : Universitätsbibliothek Heidelberg, 2019. http://d-nb.info/120260806X/34.

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Vetma, Vesna [Verfasser], and Markus [Akademischer Betreuer] Morrison. "Assessment of TRAIL sensitisation by IAP antagonist TL32711 in malignant melanoma and development of a framework for response prediction / Vesna Vetma ; Betreuer: Markus Morrison." Stuttgart : Universitätsbibliothek der Universität Stuttgart, 2020. http://d-nb.info/1212034449/34.

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Hagen, Jeffrey M. "CD31: Invasive Predictive Biomarker for Malignant Transformation of Oral Epithelial Dysplasia." The Ohio State University, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=osu1376839992.

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Hill, Alexandra. "Digital image analysis: Predictive biomarkers for chemoimmunotherapy in malignant pleural mesothelioma." Thesis, Hill, Alexandra (2019) Digital image analysis: Predictive biomarkers for chemoimmunotherapy in malignant pleural mesothelioma. Honours thesis, Murdoch University, 2019. https://researchrepository.murdoch.edu.au/id/eprint/54434/.

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Книги з теми "Prediction Of Malignant"

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Cherdanceva, Tat'yana, Vladimir Klimechev, and Igor' Bobrov. Pathological and molecular biological analysis of renal cell carcinoma. Diagnosis and prognosis. ru: INFRA-M Academic Publishing LLC., 2020. http://dx.doi.org/10.12737/1020785.

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The monograph is devoted to the study of pathomorphological and molecular-biological characteristics of renal cell carcinoma and peritumoral zone depending on the degree of malignancy, and determine prognostic significance of criteria for predicting the postoperative survival of patients. Of interest to urologists, oncologists, pathologists, researchers, graduate students, dealing with the diagnosis of renal cell carcinoma and subsequent prediction of postoperative survival of patients.
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2

McElhinney, Veronica. A study to assess the possibility of a predictive prodrome for the development of neuroleptic malignant syndrome. [S.l: The Author], 1993.

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3

Durand, Melissa A. Architectural Distortion (Cancer). Edited by Christoph I. Lee, Constance D. Lehman, and Lawrence W. Bassett. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780190270261.003.0029.

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An architectural distortion (AD) is an alteration of the breast parenchyma, which results in radiating lines or spicules emanating from a point without a distinct mass. It can occur as the primary finding, or it may be an associated feature of a mass, asymmetry, or calcifications. AD is a mammographic finding with a high positive predictive value for malignancy and is a major cause of false-negative screening exams. This chapter, appearing in the section on asymmetry, mass, and distortion, reviews the key imaging and clinical features, imaging protocols, differential diagnoses, management recommendations, and potential pitfalls for a malignant architectural distortion. Topics discussed include superimposition of breast tissue, localization, workup of tomosynthesis-detected architectural distortion, and image-guided biopsy options.
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Townsend, William M., and Emma C. Morris. ICU selection and outcome of patients with haematological malignancy. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780199600830.003.0374.

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Patients with haematological malignancies require admission to the intensive care unit (ICU) due to the underlying disease, as a consequence of treatment with chemotherapy or after haematopoietic stem cell transplantation. With an increasing numbers of patients being diagnosed with these diseases and longer survival as treatments improve, the burden on ICU is anticipated to increase. There is compelling evidence that patients should not be denied admission to ICU based on the presence of a haematological malignancy. In this chapter the disease- and treatment-related reasons for ICU admission, outcome, and risk prediction scores for patients with haematological malignancies are discussed.
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Kwon, Rachel J. Size as a Predictor of Malignancy of Adrenal Cortical Carcinoma. Edited by Randall Owen. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780199384075.003.0042.

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This chapter provides a summary of a landmark study in endocrine surgery. Does size correlate with malignancy in adrenal cortical carcinoma? Starting with that question, it describes the basics of the study, including year study began, year study was published, study location, who was studied, who was excluded, how many patients, study design, study intervention, follow-up, endpoints, results, and criticism and limitations. The chapter briefly reviews other relevant studies and information, gives a summary and discusses implications, and concludes with a relevant clinical case involving postoperative treatment of a patient with adrenocortical carcinoma who has a large adrenal incidentaloma.
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Doepke, Laura. Fine, Linear/Branching Calcifications. Edited by Christoph I. Lee, Constance D. Lehman, and Lawrence W. Bassett. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780190270261.003.0041.

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Of all of the calcifications identified on mammography, fine, linear/branching calcifications are the most suspicious for malignancy, most commonly ductal carcinoma in situ (DCIS). The risk of malignancy associated with fine, linear/branching calcifications is approximately 70%. A recent study evaluating the positive predictive value of suspicious calcifications based on the fifth edition of BI-RADS found the positive predictive value of fine pleomorphic/linear or segmental calcifications was 93.8%. This chapter, which appears in the section on calcifications, reviews the key imaging features, imaging protocols for evaluating calcifications, management, and potential pitfalls or mimics of fine, linear/branching calcifications. Topics discussed will include magnification views, stereotactic core needle biopsy, and radiology–pathology correlation.
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Prout, Jeremy, Tanya Jones, and Daniel Martin. Thoracic anaesthesia. Oxford University Press, 2014. http://dx.doi.org/10.1093/med/9780199609956.003.0015.

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Pre-assessment of patients for thoracic surgery with prediction of postoperative dyspnoea is important and may determine ‘operability’ of malignancy. Anaesthetic conduct for common thoracic surgical procedures such as thoracotomy, video-assisted thorascopic surgery, mediastinal surgery, and bronchoscopic techniques are described. Techniques for providing one-lung ventilation using double-lumen tubes or endobronchial blockers are discussed along with the physiology of one-lung ventilation, hypoxic vasoconstriction, and techniques to improve oxygenation. Thoracic postoperative care such as pain and chest drain management is included
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Sherman, Mark E., Melissa A. Troester, Katherine A. Hoadley, and William F. Anderson. Morphological and Molecular Classification of Human Cancer. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780190238667.003.0003.

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Accurate and reproducible classification of tumors is essential for clinical management, cancer surveillance, and studies of pathogenesis and etiology. Tumor classification has historically been based on the primary anatomic site or organ in which the tumor occurs and on its morphologic and histologic phenotype. While pathologic criteria are useful in predicting the average behavior of a group of tumors, histopathology alone cannot accurately predict the prognosis and treatment response of individual cancers. Traditional measures such as tumor stage and grade do not take into account molecular events that influence tumor aggressiveness or changes in the tumor composition during treatment. This chapter provides a primer on approaches that use pathology and molecular biology to classify and subclassify cancers. It describes the features of carcinomas, sarcomas, and malignant neoplasms of the immune system and blood, as well as various high-throughput genomic platforms that characterize the molecular profile of tumors.
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Andrzej, Wojcik, and Colin J. Martin. Biological effects of ionizing radiation. Oxford University Press, 2015. http://dx.doi.org/10.1093/med/9780199655212.003.0003.

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Biological effects of radiation have been interpreted based on the assumption that DNA is the primary target, but recent research has shown that non-targeted mechanisms may affect cells that are not directly exposed. The most important effect in humans from low doses of radiation is the induction of cancer, but risks of other effects such as cataract and cardiac or circulatory disease are becoming apparent. Epidemiological studies of Japanese survivors of atomic bombs demonstrate a clear linear relationship between solid cancer incidence and organ dose. This is supported by other epidemiological data. This has become the gold standard for prediction of malignancy based on a linear no-threshold ‘LNT’ extrapolation, which links risk directly to radiation dose. However, the risk calculations involve many assumptions and approximations. They are designed to provide guidance on which a workable protection framework can be based. It is important that practitioners are aware of their limitations.
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Harper, Lorraine, and David Jayne. The patient with vasculitis. Edited by Giuseppe Remuzzi. Oxford University Press, 2015. http://dx.doi.org/10.1093/med/9780199592548.003.0160.

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The goals of treatment in renal vasculitis are to stop vasculitic activity and recover renal function. Subsequent strategies are required to prevent vasculitis returning and to address longer-term co-morbidities caused by tissue damage, drug toxicity, and increased cardiovascular and malignancy risk.Cyclophosphamide and high-dose glucocorticoids remain the standard induction therapy with alternative immunosuppressives, such as azathioprine, to prevent relapse. Plasma exchange improves renal recovery in severe presentations. Refractory disease resulting from a failure of induction or remission maintenance therapy requires alternative agents and rituximab has been particularly effective. Replacement of cyclophosphamide by rituximab for remission induction is supported by recent evidence. Methotrexate is effective in non-renal vasculitis but difficult to use in patients with renal impairment. Mycophenolate mofetil seems to be effective but there is less long-term evidence.Drug toxicity contributes to co-morbidity and mortality and has led to newer regimens with reduced cyclophosphamide exposure. Glucocorticoid toxicity remains a major problem with controversy over the rapidity with which glucocorticoids can be reduced or withdrawn.Disease relapse occurs in about 50% of patients. Early detection is less likely to lead to an adverse affect on outcomes. Rates of cardiovascular disease and malignancy are higher than in control populations but strategies to reduce their risk, apart from cyclophosphamide-sparing regimens, have not been developed. Thromboembolic events occur in 10% and may be linked to the recently identified autoantibodies to plasminogen and tissue plasminogen activator.Renal impairment at diagnosis is a strong predictor of patient survival and renal outcome. Other predictors include patient age, antineutrophil cytoplasmic antibody subtype, disease extent and response to therapy. Chronic kidney disease can stabilize for many years but the risks of end-stage renal disease are increased by acute kidney injury at presentation or renal relapse. Renal transplantation is successful with similar outcomes to other causes of end-stage renal disease.
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Частини книг з теми "Prediction Of Malignant"

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Toyota, S., Rudolf Graf, M. Valentino, T. Yoshimine, and W. D. Heiss. "Prediction of malignant infarction: perifocal neurochemical monitoring following prolonged MCA occlusion in cats." In Brain Edema XII, 153–57. Vienna: Springer Vienna, 2003. http://dx.doi.org/10.1007/978-3-7091-0651-8_32.

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Madasamy, Kaliappan, Vimal Shanmuganathan, Nithish, Vishakan, Vijayabhaskar, Muthukumar, Balamurali Ramakrishnan, and M. Ramnath. "Benign and Malignant Cancer Prediction Using Deep Learning and Generating Pathologist Diagnostic Report." In Engineering Cyber-Physical Systems and Critical Infrastructures, 73–87. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-52787-6_7.

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Kumar, Vivek, Brojo Kishore Mishra, Manuel Mazzara, Dang N. H. Thanh, and Abhishek Verma. "Prediction of Malignant and Benign Breast Cancer: A Data Mining Approach in Healthcare Applications." In Advances in Data Science and Management, 435–42. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-0978-0_43.

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Anderson, Owen, Andrew C. Kidd, Keith A. Goatman, Alexander J. Weir, Jeremy P. Voisey, Vismantas Dilys, Jan P. Siebert, and Kevin G. Blyth. "Estimating the False Positive Prediction Rate in Automated Volumetric Measurements of Malignant Pleural Mesothelioma." In Biomedical Engineering Systems and Technologies, 116–39. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72379-8_7.

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Aggarwal, Ritu. "An Intelligent System for Diagnosis and Prediction of Breast Cancer Malignant Features using Machine Learning Algorithms." In Machine Learning and Deep Learning Techniques for Medical Science, 143–51. Boca Raton: CRC Press, 2022. http://dx.doi.org/10.1201/9781003217497-8.

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Sloan, Philip. "The Bi-Directional Communication Between Tumour Cells and Other Components of the Tumour Microenvironment." In Critical Issues in Head and Neck Oncology, 1–9. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-23175-9_1.

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AbstractCross talk between cancer cells and their microenvironment can lead to molecular changes in adjacent tissues that can be utilised as biomarkers. One such example stems from the discovery that malignant melanomas with metastatic potential can downregulate autophagy in the overlying epidermis. Autophagy is essential for normal keratinocyte maturation. AMBRA1 is a key autophagy regulatory molecule and its expression in the epidermis is reduced in the epidermis overlying some early stage melanomas. Expression of AMBRA1 is maintained in the overlying epidermis in a subset of low risk melanomas. This finding has been translated into a novel biomarker for clinical use. Preliminary data suggest that AMBRA1 expression in neoplastic cells may be a useful biomarker for prediction of risk of progression in oropharyngeal and cutaneous squamous cell carcinoma. It is likely that it will be necessary to combination biomarker expression with Artificial Intelligence analysis and convention staging to provide accurate individualised prognostic information for clinical use.
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Larrañaga, Pedro, Basilio Sierra, Miren J. Gallego, Maria J. Michelena, and Juan M. Picaza. "Learning Bayesian Networks by Genetic Algorithms: A case study in the prediction of survival in malignant skin melanoma." In Artificial Intelligence in Medicine, 261–72. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/bfb0029459.

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Schölmerich, Jürgen, Eckart Köttgen, Brigitte A. Volk, and Wolfgang Gerok. "Proteases and Antiproteases in Ascites — Differentiation of Malignant and Nonmalignant Ascites and Prediction of Coagulopathy in Ascites Retransfusion." In Advances in Experimental Medicine and Biology, 555–60. Boston, MA: Springer US, 1988. http://dx.doi.org/10.1007/978-1-4613-1057-0_71.

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Yhap, Margaret, Allen F. Pyesmany, Lynne M. Ball, D. Christie Riddle, Jiang Mu, and Dick van Velzen. "Microsatellite Instability Assessment in Prediction of Drug Resistance in Childhood Burkitt’s and Large Cell Diffuse Malignant Non-Hodgkin Lymphoma (MNHL)." In Drug Resistance in Leukemia and Lymphoma III, 517–25. Boston, MA: Springer US, 1999. http://dx.doi.org/10.1007/978-1-4615-4811-9_56.

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Morimoto, Yasuo, Chinatsu Nishida, Taisuke Tomonaga, and Hiroto Izumi. "Pleural Plaques as a Predictive Imaging Marker for Cancer Screening in Asbestos-Exposed Subjects: Can Pleural Plaques Be a Tool beyond Estimating Past Asbestos Inhalation?" In Malignant Pleural Mesothelioma, 65–74. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-9158-7_6.

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Тези доповідей конференцій з теми "Prediction Of Malignant"

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Sharma, Kriti, Brahmini Muktha, Apoorva Rani, and Chandrasegar Thirumalai. "Prediction of benign and malignant tumor." In 2017 International Conference on Trends in Electronics and Informatics (ICOEI). IEEE, 2017. http://dx.doi.org/10.1109/icoei.2017.8300871.

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Mittal, Veena, Chandra Kant, Kartikey Pandey, and Dinesh Pratap Singh. "Prediction of Benign or Malignant Human Cells using Artificial Intelligence." In 2021 3rd International Conference on Advances in Computing, Communication Control and Networking (ICAC3N). IEEE, 2021. http://dx.doi.org/10.1109/icac3n53548.2021.9725525.

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Gao, Zixiong, Yufan Chen, Wuping Mai, Yao Lu, Shuyu Wu, and Hongmei Liu. "Multi-task learning of perceptive feature for thyroid malignant probability prediction." In Computer-Aided Diagnosis, edited by Karen Drukker and Maciej A. Mazurowski. SPIE, 2021. http://dx.doi.org/10.1117/12.2580697.

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Ma, Yue, Lin Liu, Jiayan Liu, Kaiming Xue, Zhe Zhou, and Mengchao Zhang. "Prediction of Benign and Malignant Thymic Tumors based on Radiomics Features." In 2019 IEEE International Conference on Mechatronics and Automation (ICMA). IEEE, 2019. http://dx.doi.org/10.1109/icma.2019.8816280.

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Kamarudin, Saddam, Ishkrizat Taib, Maliki Adnan, Fitriah Nasir, Ahmad Mubarak Tajul Ariffin, Nor Adrian Nor Salim, Nofrizal Idris Darlis, Mohd Noor Abdullah, and Ali Kamil. "Prediction of heat distribution on brain malignant tumor using hyperthermia therapy." In 12th INTERNATIONAL CONFERENCE ON MECHANICAL AND MANUFACTURING ENGINEERING 2022 (ICME’22). AIP Publishing, 2023. http://dx.doi.org/10.1063/5.0183646.

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Promtan, Santad, Phungern Khongthong, and Chidchanok Choksuchat. "Breast Cancer Prediction of Benign and Malignant Tumors by Classification Algorithms." In 2023 4th International Conference on Big Data Analytics and Practices (IBDAP). IEEE, 2023. http://dx.doi.org/10.1109/ibdap58581.2023.10271967.

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Goh, Jasmine, Sanjay de Mel, Anand D. Jeyasekharan, and Edward K. H. Chow. "Abstract PO-51: Drug combination analytics platform for accurate prediction of treatment response in refractory and relapsed lymphomas." In Abstracts: AACR Virtual Meeting: Advances in Malignant Lymphoma; August 17-19, 2020. American Association for Cancer Research, 2020. http://dx.doi.org/10.1158/2643-3249.lymphoma20-po-51.

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Wei Heng, Wei, Eileen Su Lee Ming, Ahmad Nizar Jamaluddin, Fauzan Khairi Che Harun, Nurul Ashikin Abdul-Kadir, and Che Fai Yeong. "Prediction Algorithm of Malignant Ventricular Arrhythmia Validated across Multiple Online Public Databases." In 2019 Computing in Cardiology Conference. Computing in Cardiology, 2019. http://dx.doi.org/10.22489/cinc.2019.295.

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Leng, William Mok Wen, Wei Wei Heng, and Nurul Ashikin Abdul-Kadir. "Earlier Prediction Algorithm of Malignant Ventricular Arrhythmia on Heterogenous Databases: A Review." In 2022 2nd International Conference on Intelligent Cybernetics Technology & Applications (ICICyTA). IEEE, 2022. http://dx.doi.org/10.1109/icicyta57421.2022.10037936.

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Wang, Jun, Xia Liu, Di Dong, Jiangdian Song, Min Xu, Yali Zang, and Jie Tian. "Prediction of malignant and benign of lung tumor using a quantitative radiomic method." In 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, 2016. http://dx.doi.org/10.1109/embc.2016.7590938.

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Звіти організацій з теми "Prediction Of Malignant"

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Huang, Wei, Dahong Yang, Danyang Fan, Chao Hou, and Wanqian Liu. Prognostic value of net water uptake in acute ischemic stroke: a protocol for a systematic review and meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, December 2021. http://dx.doi.org/10.37766/inplasy2021.12.0077.

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Review question / Objective: The purpose of this protocol is to present a transparent and clear methodology for performing a systematic review and meta-analysis of the available literature aimed to answer the following question: among patients with acute ischemic stroke due to large vessel occlusion, is net water uptake (NWU), as measured in CT images, associated with (i) cerebrovascular complications, including malignant cerebral edema, secondary intracerebral hemorrhage, and (ii) post-stroke functional outcome as measured by the modified Rankin Scale. Condition being studied: Currently, the association between net water uptake with cerebrovascular complications or post-stroke functional outcomes is not well defined. Broocks found that NWU based on CT was an important marker for malignant edema in LVO patients and independently associated with clinical prognosis. Additionally, Nawabi indicated that a higher degree of NWU was a predictor of intracranial hemorrhage in patients with acute ischemic stroke treated with mechanical thrombectomy. Thus, a higher NWU might contribute to the development of stroke complications and poorer outcomes. However, no systematic review and meta-analysis to quantitatively summarize this evidence and help establish the predictive value of NWU in patients with acute ischemic stroke.
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2

Gareau, Paul, and Brian K. Rutt. Prediction of Malignancy in Breast Tumors Using Diffusion Weighted Magnetic Resonance Imaging. Fort Belvoir, VA: Defense Technical Information Center, July 2000. http://dx.doi.org/10.21236/ada390993.

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Lochab, Dr Prachi, Dr Lata Rajoria, Dr Sunita Hemani, and Dr Akanksha Akanksha. EVALUATION OF IOTA SIMPLE ULTRASOUND RULES AND HISTOPATHOLOGY TO DISTINGUISH BETWEEN BENIGN AND MALIGNANT OVARIAN TUMORS : A DESCRIPTIVE STUDY. World Wide Journals, February 2023. http://dx.doi.org/10.36106/ijar/5405931.

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Introduction: Ovarian masses present with very vague symptoms and thus it is imperative to establish a quick diagnosis at the rst point of contact. Pre-operative diagnosis of an ovarian mass and its classication as benign or malignant helps in timely referral to specialized gynecologist/oncologist and proper surgical/medical management. IOTA simple Rules provides one such criteria for pre-operative classication of ovarian mass and has proved to be reliable, accurate and highly reproducible in all settings. a hospital Methods: based prospective study was done on 100 patients. Initial pre-operative classication was done using IOTA Simple Rules and the ndings were compared to histo-pathological ndings after surgery which were considered gold standard. Out of the 100 masses under study, 86% Results: could be classied according to IOTA Simple Rules with a sensitivity of 96.36% and specicity of 91.4%. The positive predictive value was 80.3% and the negative predictive value was 94.1%. The accuracy was 85%. Thus, IOTA S Conclusion: imple Rules is a cost-effective, simple, reliable, accurate scoring system with excellent sensitivity and specicity that is easily applicable in primary evaluation of patients with ovarian masses in clinical practice. Only unclassied masses on IOTA Simple Rules need further evaluation. Use of these rules in discriminating the masses will help in timely referral of the patient to specialized gynecologist /oncologist to receive optimal management.
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Li, Yu, Yi-Biing Shi, and Chun-Feng Hu. PET/CT based model for predicting malignancy in pulmonary nodules: a meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, October 2023. http://dx.doi.org/10.37766/inplasy2023.10.0042.

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Bai, Tian, Li-Juan Wen, and Na Zhang. Predictive model for the probability of malignancy in solitary pulmonary nodules: A meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, October 2021. http://dx.doi.org/10.37766/inplasy2021.10.0006.

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