Gotowe bibliografie tematyczne / Predictive factors

Gotowa bibliografia na temat „Predictive factors”

Autor: Grafiati
Data publikacji: 4 czerwca 2021
Data aktualizacji: 21 lutego 2023

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Artykuły w czasopismach na temat "Predictive factors"

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Chocce, John, Donald A. Johnson i Yossiri Yossatorn. "Predictive Factors of Freshmen’s Intercultural Sensitivity". International Journal of Information and Education Technology 5, nr 10 (2015): 778–82. http://dx.doi.org/10.7763/ijiet.2015.v5.610.

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Al-Nefaie, Mamdouh Mohammed Zowaid. "Prevalence and Predictive Risk Factors of Hypertension". International Journal Of Pharmaceutical And Bio-Medical Science 02, nr 11 (17.11.2022): 518–23. http://dx.doi.org/10.47191/ijpbms/v2-i11-08.

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Worldwide, the prevalence of diseases caused by and related to hypertension is rising. The goal of the current study was to investigate the causes of hypertension in hospital inpatients receiving tertiary care. Patient information was gathered, including demographics, laboratory results, and the final diagnosis. The six-month study, which involved 160 patients overall, was conducted. 20% did not have hypertension, making up the remaining 80%. Between the hypertensive and non-hypertensive population, risk factors for hypertension such as smoking, alcohol use, demographics, socioeconomic status, diet, family history, family size, education level, salt intake, lifestyle, and basic metabolic index were compared. In the study population, it was discovered that drinking alcohol, smoking, and eating a varied diet were significant risk factors for hypertension. As a result, these factors can be taken into account when creating effective prevention strategies and management guidelines for hypertension at the study site.
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van Leeuwen, R. B., P. H. Hoogland i A. W. de Weerd. "Chemonucleolysis; Predictive Factors". Spine 17, nr 7 (lipiec 1992): 838–41. http://dx.doi.org/10.1097/00007632-199207000-00019.

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Köhne, Claus-Henning, Udo Vanhoefer i Gernot Hartung. "Clinical predictive factors". European Journal of Cancer 45 (wrzesień 2009): 43–49. http://dx.doi.org/10.1016/s0959-8049(09)70015-2.

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Wang, Hsin-Yao, Yu-Hsin Liu, Yi-Ju Tseng, Chia-Ru Chung, Ting-Wei Lin, Jia-Ruei Yu, Yhu-Chering Huang i Jang-Jih Lu. "Investigating Unfavorable Factors That Impede MALDI-TOF-Based AI in Predicting Antibiotic Resistance". Diagnostics 12, nr 2 (5.02.2022): 413. http://dx.doi.org/10.3390/diagnostics12020413.

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The combination of Matrix-Assisted Laser Desorption/Ionization Time-of-Flight (MALDI-TOF) spectra data and artificial intelligence (AI) has been introduced for rapid prediction on antibiotic susceptibility testing (AST) of Staphylococcus aureus. Based on the AI predictive probability, cases with probabilities between the low and high cut-offs are defined as being in the “grey zone”. We aimed to investigate the underlying reasons of unconfident (grey zone) or wrong predictive AST. In total, 479 S. aureus isolates were collected and analyzed by MALDI-TOF, and AST prediction and standard AST were obtained in a tertiary medical center. The predictions were categorized as correct-prediction group, wrong-prediction group, and grey-zone group. We analyzed the association between the predictive results and the demographic data, spectral data, and strain types. For methicillin-resistant S. aureus (MRSA), a larger cefoxitin zone size was found in the wrong-prediction group. Multilocus sequence typing of the MRSA isolates in the grey-zone group revealed that uncommon strain types comprised 80%. Of the methicillin-susceptible S. aureus (MSSA) isolates in the grey-zone group, the majority (60%) comprised over 10 different strain types. In predicting AST based on MALDI-TOF AI, uncommon strains and high diversity contribute to suboptimal predictive performance.
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M. Ahmed, Shyaw, Lusan A. Arkawazi i Kawa A. Mahmood. "SURGICAL SPERM RETRIEVAL IN AZOOSPERMIA: OUTCOME AND PREDICTIVE FACTORS". Journal of Sulaimani Medical College 11, nr 2 (21.06.2021): 129–37. http://dx.doi.org/10.17656/jsmc.10295.

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Dixon, A. A., R. O. Holness, W. J. Howes i J. B. Garner. "Spontaneous Intracerebral Haemorrhage: An Analysis of Factors Affecting Prognosis". Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques 12, nr 3 (sierpień 1985): 267–71. http://dx.doi.org/10.1017/s0317167100047144.

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ABSTRACT:A retrospective study of 100 patients with spontaneous intracerebral haemorrhage was carried out, to identify clinical factors which have a predictive value for outcome. Numerical equivalents for the admission level of consciousness (the Glasgow Coma Scale), ventricular rupture, partial pressure of oxygen in the blood, the electrocardiogram, clot location, and clot size were combined into equations predicting outcome. The best single parameter for prediction was the Glasgow Coma Scale.
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Dragicevic, S., D. Djordjevic, V. Andrejevic, D. Perovic, N. Lalic i S. Micic. "S65 VARICOCELETOMY: PREDICTIVE FACTORS". European Urology Supplements 11, nr 4 (październik 2012): 149. http://dx.doi.org/10.1016/s1569-9056(13)60259-6.

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Gafarov, F. M., Ya B. Rudneva i U. Yu Sharifov. "Predictive Modeling in Higher Education: Determining Factors of Academic Performance". Vysshee Obrazovanie v Rossii = Higher Education in Russia 32, nr 1 (21.01.2023): 51–70. http://dx.doi.org/10.31992/0869-3617-2023-32-1-51-70.

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For several decades in the field of data mining in education (EDM), predictive learning has remained one of the most popular and internationally discussed research topics. Specifically, data mining is used to predict educational outcomes such as academic performance, retention, success, satisfaction, achievement and dropout rates. In the management practice of higher education institutions, on the basis of an operational forecast, measures are developed and implemented to support those students who fall into the risk group.Our study is aimed at substantiating a model for predicting the early departure of students using an artificial neural network and analyzing predictors that increase the accuracy of predicting successful graduation from a Russian university. This work will expand the international practice of comparative research in higher education.The paper confirms the already existing hypotheses about the influence of a number of factors on the prediction of academic performance and suggests the need to test their universality or specificity in a particular institution of higher education. We also proved that an artificial neural network model with a certain set of attributes can be applied in the context of a single higher education institution, regardless of specialization. To determine the potential risk group of students, a binary classification prediction model is used. The overall prediction accuracy of a neural network with combined data reaches 88%. For this neural network model, the basic predictors that affect the accuracy of the forecast are the cumulative average level of achievement (CGPA) and the year of admission to the university.
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Mehta, Nirali, R. G. Bhatt, Hetal Vora i Dlvya Reddy. "Predischarge risk factors for predicting significant hyperbilirubinemia in term of infants". International Journal of Contemporary Pediatrics 6, nr 2 (23.02.2019): 315. http://dx.doi.org/10.18203/2349-3291.ijcp20190526.

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Background: The objective of the study to compare the predictive ability of predischarge serum total bilirubin (STB) and clinical factors for significant hyperbilirubinemia (SHB) in newborn to observe the prediction of the hyperbilirubinemia.Methods: In the prospective study, enlist of healthy newborn infants with >35 weeks gestation, in a tertiary hospital in western India. The serum bilirubin between 36-48 hours of age and risk factors for SHB were identified before discharge. SHB was distinct as a bilirubin level that exceed or was within 1mg/dL (17µmol/L) of the hour-specific phototherapy conduct threshold recommended by American Academy of Pediatrics (AAP) guideline on the management of neonatal hyperbilirubinemia.Results: Of 505 infants, 380 infants were included in final analysis, among which 70 babies (22.5%) developed SHB. On univariate analysis STB, gestational age (GA) and percentage of weight loss were found to be predictive of SHB. On multiple logistic regressions, the prognostic ability of predischarge STB is higher than that of percentage of weight loss and GA. The predictive accurateness of predischarge (<48 hours) STB level was comparable to that of percentage of weight loss (AUC=0.88, 95% CI 0.84-0.93). However, the prediction model that combined multiple risk factors such as predischarge STB, GA and percentage of weight loss have the best accuracy for predicting SHB.Conclusions: Combination of specific clinical factors (gestational age and percentage of weight loss) with predischarge serum total bilirubin described best predicts development of considerable hyperbilirubinemia.
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Rozprawy doktorskie na temat "Predictive factors"

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Dreilich, Martin. "Predictive Factors in Esophageal Carcinoma". Doctoral thesis, Uppsala : Acta Universitatis Upsaliensis : Univ.-bibl. [distributör], 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-6831.

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Tibau, Martorell Ariadna. "marcadors biològics predictius de resposta a la quimioteràpia primària (neoadjuvant) amb antraciclines i taxans". Doctoral thesis, Universitat Autònoma de Barcelona, 2016. http://hdl.handle.net/10803/399842.

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Predir la resposta a la quimioteràpia és un repte fonamental en el tractament de pacients amb càncer de mama. El benefici de la quimioteràpia amb antraciclines i taxans en càncer de mama precoç és modest i els efectes secundaris a llarg termini no desdenyables. La identificació de factors predictius de resposta permetria millorar l'eficàcia de la quimioteràpia i minimitzar les toxicitats secundàries. Actualment no disposem de biomarcadors específics per predir la resposta del tumor a la quimioteràpia amb antraciclines i taxans. L’amplificació del gen Human epidermal growth factor receptor 2 (HER2), la topoisomerasa II alfa (TOP2A) i la duplicació del centròmer del cromosoma 17 (CEP17) s’han proposats com a biomarcadors predictius de resposta a les antraciclines mentre que una expressió disminuïda de la proteïna Tau i dels isotips I a IV de la β-tubulina s’han relacionat amb la resposta a la quimioteràpia amb taxans. Els resultats dels estudis són discordants i cap d’aquests biomarcadors tumorals pot ser considerat un marcador predictiu de resposta a les antraciclines i taxans. En el present estudi s’han analizat aquests potencials marcadors predictius de resposta al tractament en una cohort de 140 pacients amb càncer de mama estadis II i III tractades amb quimioteràpia neoadjuvant amb antraciclines i taxans, emprant la resposta completa patològica com a marcador subrogat de quimiosensibilitat. Posteriorment s'ha avaluat el seu impacte en la supervivència. Els resultats d’aquesta tesi demostren: que la duplicació del CEP17 prediu la resposta completa patològica en pacients amb càncer de mama tractades amb esquemes de quimioteràpia basades en antraciclines, i que la baixa expressió de la proteïna Tau s’associa a la resposta a la quimioteràpia neoadjuvant i al benefici amb taxans. Les pacients amb alta expressió de la proteïna Tau tenen millor pronòstic.
Predicting response to chemotherapy is a central challenge in treating patients with breast cancer. Anthracycline–taxane-based chemotherapy produces a modest improvement in survival for women with early-stage breast cancer. However, these drugs are associated with serious side-effects and careful selection is needed to ensure that they are given only to patients who may benefit from them. To date, no specific biomarkers have been identified to predict tumor response to anthracycline-taxane-based chemotherapy. Human epidermal growth factor receptor 2 (HER2), topoisomerase II alpha (TOP2A) genes and chromosome 17 centromere enumeration probe (CEP17) duplication have all been proposed as predictive biomarkers of anthracycline treatment, whereas low expression of the microtubule-associated protein Tau and classes I to IV β-tubulin isotypes has been linked to better response to taxane chemotherapy. However, reports are conflicting, and none of these tumor markers can yet be considered a clinically reliable predictor of response to anthracycline–taxane-based chemotherapy. We studied the predictive and prognostic value of TOP2A gene alterations, HER2 gene amplification, CEP17 duplication and Tau protein expression, as well as classes I to IV β-tubulin isotypes expression in 140 patients with operable or locally advanced breast cancer receiving anthracycline-taxane-based neoadjuvant chemotherapy. The results of this thesis show that: CEP17 duplication predicts pathologic complete response to primary anthracycline-based chemotherapy, and low Tau protein expression is associated with response to neoadjuvant chemotherapy and taxane benefit. Patients with high Tau expression have a better prognosis.
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Hemdan, Tammer. "Prognostic and Predictive Factors in Bladder Cancer". Doctoral thesis, Uppsala universitet, Urologkirurgi, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-282607.

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Bladder cancer is a potentially curable malignancy; however in regards to the state of current therapy regimens, a plateau has been reached in both the non-muscle and muscle invasive types. To obtain effective treatment, and consequently a decreased mortality, it has become imperative to test and understand aspects affecting therapy response. The aim of this thesis is to illustrate a better understanding of clinical factors affecting therapy response using new drug combinations and new tumor markers alongside established risk criteria. In Paper I we reported the 5 year follow up from a multicenter, prospectively randomized study and we evaluated the 5-year outcomes of BCG alone compared to a combination of epirubicin and interferon-a2b in the treatment of patients with T1 bladder cancer. Treatment, tumor size and tumor status at second resection were independent variables associated with recurrence. Concomitant Cis was not predictive of failure of BCG therapy. Independent factor for treatment failure was remaining T1 stage at second resection. In Paper II &III we investigated the validity of emmprin, survivin and CCTα proteins as biomarkers for response and survival before neoadjuvant cisplatin chemotherapy. Bladder tumor specimens were obtained before therapy from a total of 250 patients with T1-T4 bladder cancer enrolled in 2 randomized trials comparing neoadjuvant chemotherapy before cystectomy with a surgery only arm. Protein expression was determined by immunohistochemistry (IHC). Patients in the chemotherapy cohort with negative emmprin and CCTα expression had significantly better overall survival (OS) than those with positive expression. In Paper IV primary end point was examining STMN1 as prognostic factor in bladder cancer.  Analysis was performed on three bladder cancer patient cohorts using IHC, western blot and a bladder cancer cell line. High levels of STMN1, expression correlated to shorter disease-specific survival and the growth and migration of the cells were significantly reduced when transfecting the cells with STMN1 siRNA. Conclusion Risk assessment and predictors of outcomes could help in individualized treatment and follow up.  Biomarkers will become more important for treatment choices in bladder cancer management.
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Derwinger, Kristoffer. "Prognostic and predictive factors in colorectal cancer /". Göteborg : Dept. of Surgery, Sahlgrenska University Hospital/Östra, 2009. http://hdl.handle.net/2077/19365.

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Robinson, Teresa Michelle. "Predictive Factors of Compassion Fatigue Among Firefighters". ScholarWorks, 2016. https://scholarworks.waldenu.edu/dissertations/2332.

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Few existing studies have examined compassion fatigue among emergency responders even though firefighters and emergency medical service (EMS) professionals have repetitive direct exposure to traumatic events. This study focused on identifying predictor variables for the development of compassion fatigue in firefighters. Karasek's demand-control model, a commonly used work stress model, was the study's theoretical framework as it focuses on specific construct interactions that predict employee well-being. Accordingly, this correlational study examined the predictive nature of EMS license level, years of service, and personality type on the development of compassion fatigue in career firefighters. Data collection occurred with surveys incorporating the Professional Quality of Life Scale and the Big Five Inventory. Mid-Michigan fire departments participated with 129 career firefighters returning completed surveys with results analyzed using logistic regression. Findings revealed a significant predictive relationship between personality traits and the development of compassion fatigue. These findings can inform preventative measures that protect the psychological well-being of these emergency responders by informing and educating the professionals and organizations as to who is at greatest risk and ultimately providing opportunity for risk mediation.
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Vanichbuncha, Tita. "Risk Factors and Predictive Modeling for Aortic Aneurysm". Thesis, Linköpings universitet, Statistik, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-80391.

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In 1963 – 1965, a large-scale health screening survey was undertaken in Sweden and this data set was linked to data from the national cause of death register. The data set involved more than 60,000 participants whose age at death less than 80 years. During the follow-up period until 2007, a total of 437 (338 males and 99 females) participants died from aortic aneurysm. The survival analysis, continuation ratio model, and logistic regression were applied in order to identify significant risk factors. The Cox regression after stratification for AGE revealed that SEX, Blood Diastolic Pressure (BDP), and Beta-lipoprotein (BLP) were the most significant risk factors, followed by Cholesterol (KOL), Sialic Acid (SIA), height, Glutamic Oxalactic Transaminase, Urinary glucose (URIN_SOC), and Blood Systolic Pressure (BSP). Moreover, SEX and BDP were found as risk factors in almost every age group. Furthermore, BDP was strongly significant in both male and female subgroup.   The data set was divided into two sets: 70 percent for the training set and 30 percent for the test set in order to find the best technique for predicting aortic aneurysm. Five techniques were implemented: the Cox regression, the continuation ratio model, the logistic regression, the back-propagated artificial neural network, and the decision tree. The performance of each technique was evaluated by using area under the receiver operating characteristic curve. In our study, the continuation ratio and the logistic regression outperformed among the other techniques.
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Houston, Kelly Charlene. "Maternal prenatal attachment : the role of predictive factors". Thesis, University of Sheffield, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.421025.

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Hupperets, Pierre Stefanus Gerardus Johannes. "Prognostic and predictive factors in primary breast cancer". Maastricht : Maastricht : Universitaire Pers Maastricht ; University Library, Maastricht University [Host], 1995. http://arno.unimaas.nl/show.cgi?fid=8354.

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Enthoven, Paul. "Back pain : long-term course and predictive factors /". Linköping : Linköpings universitet, 2005. http://www.bibl.liu.se/liupubl/disp/disp2005/med881s.pdf.

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Adlard, Julian Weldon. "Colorectal cancer : predictive factors for response to chemotherapy". Thesis, University of Leeds, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.415610.

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Książki na temat "Predictive factors"

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M, Thompson Alastair, red. Prognostic and predictive factors in breast cancer. Wyd. 2. London: Informa Healthcare, 2008.

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Ries, Allen Arthur. Predictive factors for bacteremia in outpatient adults. [New Haven: s.n.], 1986.

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Prognostic and predictive factors in breast cancer. London: Martin Dunitz, 2003.

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Miettinen, Timo. Whiplash injuries in Finland: Incidence, prognosis and predictive factors for the long-term outcome. Kuopio: Kuopion yliopisto, 2005.

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Isaacs, Josephine Elizabeth. An investigation of predictive factors of pyschological morbidity in burn injuredpatients three months post burn. Manchester: University of Manchester, 1996.

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Kenedy, Beatrice Patricia. Factors predictive of the granting of a nullity decree in a Catholic Church Regional Marriage Tribunal in Ireland. Dublin: University College Dublin, 1997.

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Will, Thorsten. Predicting Transcription Factor Complexes. Wiesbaden: Springer Fachmedien Wiesbaden, 2015. http://dx.doi.org/10.1007/978-3-658-08269-7.

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W, Maris Ronald, i American Association of Suicidology, red. Assessment and Prediction of Suicide. New York: Guilford Press, 1992.

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Gillespie, Maggie. Factors affecting student persistence: A longitudinal study. Iowa City, Iowa: American College Testing Program, 1992.

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Gillespie, Maggie. Factors affecting student persistence: A longitudinal study. Iowa City, Iowa: American College Testing Program, 1992.

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Części książek na temat "Predictive factors"

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Muthuraj, R. Jeromia, A. Mohamed Ashik i A. Loganathan. "Statistical Methodology for Software Reliability with Environmental Factors". W Predictive Analytics, 227–59. First edition. | Boca Raton, FL : CRC Press/Taylor & Francis Group, LLC, 2021. | Series: Advanced research in reliability and system assurance engineering: CRC Press, 2020. http://dx.doi.org/10.1201/9781003083177-14.

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Kuhn, Max, i Kjell Johnson. "Factors That Can Affect Model Performance". W Applied Predictive Modeling, 521–46. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-6849-3_20.

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Tuzlali, Sitki, i Ekrem Yavuz. "Prognostic and Predictive Factors". W Breast Disease, 163–72. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-04606-4_11.

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Biganzoli, Laura. "Prognostic and Predictive Factors". W Adjuvant Therapy for Breast Cancer, 13–30. Boston, MA: Springer US, 2009. http://dx.doi.org/10.1007/978-0-387-75115-3_2.

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Tuzlali, Sitki, i Ekrem Yavuz. "Prognostic and Predictive Factors". W Breast Cancer, 171–86. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-96947-3_6.

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Alanyalı, Senem Demirci. "Prognostic and Predictive Factors". W Principles and Practice of Modern Radiotherapy Techniques in Breast Cancer, 35–47. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-5116-7_4.

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Ku, Jerry, i Jefferson R. Wilson. "Factors Predictive of Operative Outcome". W Degenerative Cervical Myelopathy and Radiculopathy, 167–76. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-97952-6_15.

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Parati, Gianfranco, Juan Eugenio Ochoa, Carolina Lombardi i Grzegorz Bilo. "Predictive Factors for White-Coat Hypertension". W White Coat Hypertension, 61–78. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-07410-8_4.

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Amy, Sliva, Neil Reilly Scott, Chamberlain John i Casstevens Randy. "16 Validating Causal and Predictive Claims in Sociocultural Models". W Human Factors and Ergonomics, 315–34. Taylor & Francis Group, 6000 Broken Sound Parkway NW, Suite 300, Boca Raton, FL 33487-2742: CRC Press, 2016. http://dx.doi.org/10.1201/9781315369587-17.

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Shen, Meng-Chun Susan, I.-Tien Chu i Wan-Tran Huang. "Factors Affecting Consumer Visiting Spa Shop: A Case in Taiwan". W Predictive Econometrics and Big Data, 563–72. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-70942-0_40.

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Streszczenia konferencji na temat "Predictive factors"

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Diaz De Teran Lopez, Teresa, Laura Sanchez Moreno, Kimberley Lee, Cristina Magadan Alvarez, Victor Mora Cuesta, Sara Naranjo Gozalo, Beatriz Abascal Bolado i in. "Prognostic factors in lung cancer:is age an independent predictive factor?" W ERS International Congress 2019 abstracts. European Respiratory Society, 2019. http://dx.doi.org/10.1183/13993003.congress-2019.pa3045.

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Calaras, Diana, Oxana Munteanu, Zinaida Luchian, Aliona David i Victor Botnaru. "Outcome predictive factors in patients with sarcoidosis". W ERS International Congress 2017 abstracts. European Respiratory Society, 2017. http://dx.doi.org/10.1183/1393003.congress-2017.pa3262.

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Taniguchi, Yoshihiko, Chikatoshi Sugimoto, Toru Arai, Taisuke Tsuji, Kazunobu Tachibana, Masanori Akira, Masanori Kitaichi, Seiji Hayashi i Yoshikazu Inoue. "Recurrence predictive factors of cryptogenic organizing pneumonia". W Annual Congress 2015. European Respiratory Society, 2015. http://dx.doi.org/10.1183/13993003.congress-2015.pa3804.

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Balashankar, Ananth, Sunandan Chakraborty, Samuel Fraiberger i Lakshminarayanan Subramanian. "Identifying Predictive Causal Factors from News Streams". W Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Stroudsburg, PA, USA: Association for Computational Linguistics, 2019. http://dx.doi.org/10.18653/v1/d19-1238.

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Takeuchi, Naoko, Toru Arai, Yumiko Sasaki, Yoshinobu Matsuda, Kanako Katayama, Chikatoshi Sugimoto, Kazunobu Tachibana i in. "Relapse predictive factors of chronic eosinophilic pneumonia". W ERS International Congress 2018 abstracts. European Respiratory Society, 2018. http://dx.doi.org/10.1183/13993003.congress-2018.pa3025.

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Ben Saad, Ahmed, Rania Kaddoussi, Asma Migaou, Nesrine Fahem, Samah Joobeur, Saousen Cheikh Mhamed i Naceur Rouatbi. "Predictive factors of bronchiectasis acute exacerbation severity". W ERS International Congress 2021 abstracts. European Respiratory Society, 2021. http://dx.doi.org/10.1183/13993003.congress-2021.pa2077.

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Anuzis, Andrius, i Kevin O. Lillehei. "Predictive Factors for Surgical Intervention in Prolactinomas". W 31st Annual Meeting North American Skull Base Society. Georg Thieme Verlag KG, 2022. http://dx.doi.org/10.1055/s-0042-1743763.

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Magalhaes, R., B. Rosa, MJ Moreira i J. Cotter. "PREDICTING AN INAPPROPRIATE COLON CAPSULE CLEANSING: A STUDY APPROACHING PREDICTIVE FACTORS". W ESGE Days. © Georg Thieme Verlag KG, 2020. http://dx.doi.org/10.1055/s-0040-1704855.

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Ayari, M., Y. Zaimi, E. Bel Hadj Mabrouk, A. Mensi, S. Ayadi, Y. Said, L. Mouelhi i R. Dabbeche. "Predictive Factors of Esophageal Varices Band Ligation Failure". W ESGE Days 2021. Georg Thieme Verlag KG, 2021. http://dx.doi.org/10.1055/s-0041-1724545.

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Bouchabou, B., S. Laabidi, M. Kefi, M. Ghribi, H. Ben nejma, W. Bougassas i R. Ennaifer. "Tolerance Of Colonoscopy Without Anesthesia: Any Predictive Factors?" W ESGE Days 2021. Georg Thieme Verlag KG, 2021. http://dx.doi.org/10.1055/s-0041-1724892.

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Raporty organizacyjne na temat "Predictive factors"

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Manosroi, Worapaka, Pichitchai Atthakomol, Piti Inthaphan i phichayut Phinyo. Predictive factors of clinical cure after adrenalectomy in primary aldosteronism. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, kwiecień 2022. http://dx.doi.org/10.37766/inplasy2022.4.0129.

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Méndez-Vizcaíno, Juan C., Alexander Guarín, César Anzola-Bravo i Anderson Grajales-Olarte. Characterizing and Communicating the Balance of Risks of Macroeconomic Forecasts: A Predictive Density Approach for Colombia. Banco de la República, październik 2021. http://dx.doi.org/10.32468/be.1178.

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Since July 2021, Banco de la República strengthened its forecasting process and communication instruments, by involving predictive densities on the projections of its models, PATACON and 4GM. This paper presents the main theoretical and empirical elements of the predictive density approach for macroeconomic forecasting. This model-based methodology allows to characterize the balance of risks of the economy, and quantify their effects through a joint probability distribution of forecasts. We estimate this distribution based on the simulation of DSGE models, preserving the general equilibrium relationships and their macroeconomic consistency. We also illustrate the technical criteria used to represent the prospective factors of risk through the probability distributions of shocks.
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Seale, Maria, Natàlia Garcia-Reyero, R. Salter i Alicia Ruvinsky. An epigenetic modeling approach for adaptive prognostics of engineered systems. Engineer Research and Development Center (U.S.), lipiec 2021. http://dx.doi.org/10.21079/11681/41282.

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Prognostics and health management (PHM) frameworks are widely used in engineered systems, such as manufacturing equipment, aircraft, and vehicles, to improve reliability, maintainability, and safety. Prognostic information for impending failures and remaining useful life is essential to inform decision-making by enabling cost versus risk estimates of maintenance actions. These estimates are generally provided by physics-based or data-driven models developed on historical information. Although current models provide some predictive capabilities, the ability to represent individualized dynamic factors that affect system health is limited. To address these shortcomings, we examine the biological phenomenon of epigenetics. Epigenetics provides insight into how environmental factors affect genetic expression in an organism, providing system health information that can be useful for predictions of future state. The means by which environmental factors influence epigenetic modifications leading to observable traits can be correlated to circumstances affecting system health. In this paper, we investigate the general parallels between the biological effects of epigenetic changes on cellular DNA to the influences leading to either system degradation and compromise, or improved system health. We also review a variety of epigenetic computational models and concepts, and present a general modeling framework to support adaptive system prognostics.
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Naumann, Keith C. Meteorological Factors ...Predicting Mission Success. Fort Belvoir, VA: Defense Technical Information Center, maj 1996. http://dx.doi.org/10.21236/ada312163.

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Hunt, Will, i Jacqueline O'Reilly. Rapid Recruitment in Retail: Leveraging AI in the hiring of hourly paid frontline associates during the Covid-19 Pandemic. Digital Futures at Work Research Centre, marzec 2022. http://dx.doi.org/10.20919/alnb9606.

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Increased demand due to the Coronavirus pandemic created the need for Walmart to onboard tens of thousands of workers in a short period. This acted as a catalyst for Walmart to bring forward existing plans to update the hiring system for store-level hourly paid associates in its US stores. The Rapid Recruitment project sought to make hiring safer, faster, fairer and more effective by removing in-person interviews and leveraging machine learning and predictive analytics. This working paper reports on a case study of the Rapid Recruitment project involving semi-structured qualitative interviews with members of the project team and hiring staff at five US stores. The research finds that while implementation of the changes had been successful and the changes were largely valued by hiring staff, lack of awareness and confidence in some changes threatened to undermine some of the objectives of the changes. Reservations about the pre-employment assessment and the algorithm’s ability to predict quality hires led someusers reviewing more applications than perhaps necessary and potentially undermining prediction of 90-day turnover. Concerns about the ability to assess candidates over the phone meant that some users had reverted to in-person interviews, raising the riskof Covid transmission and potentially undermining the objective of removing the influence of human bias linked to appearance and other factors unrelated to performance. The impact of awareness and confidence in the changes to the hiring system are discussed in relation to the project objectives
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Liu, Xiaopei, Dan Liu i Cong’e Tan. Gut microbiome-based machine learning for diagnostic prediction of liver fibrosis and cirrhosis: a systematic review and meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, maj 2022. http://dx.doi.org/10.37766/inplasy2022.5.0133.

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Review question / Objective: The invasive liver biopsy is the gold standard for the diagnosis of liver cirrhosis. Other non-invasive diagnostic approaches, have been used as alternatives to liver biopsy, however, these methods cannot identify the pathological grade of the lesion. Recently, studies have shown that gut microbiome-based machine learning can be used as a non-invasive diagnostic approach for liver cirrhosis or fibrosis, while it lacks evidence-based support. Therefore, we performed this systematic review and meta-analysis to evaluate its predictive diagnostic value in liver cirrhosis or fibrosis. Condition being studied: Liver fibrosis and cirrhosis. Liver fibrosis refers to excessive deposition of liver fibrous tissue caused by various pathogenic factors, such as hepatitis virus, alcohol, and drug-induced chemical injury. Continuous progression of liver fibrosis can lead to liver cirrhosis.
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Mathew, Sonu, Srinivas S. Pulugurtha i Sarvani Duvvuri. Modeling and Predicting Geospatial Teen Crash Frequency. Mineta Transportation Institute, czerwiec 2022. http://dx.doi.org/10.31979/mti.2022.2119.

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This research project 1) evaluates the effect of road network, demographic, and land use characteristics on road crashes involving teen drivers, and, 2) develops and compares the predictability of local and global regression models in estimating teen crash frequency. The team considered data for 201 spatially distributed road segments in Mecklenburg County, North Carolina, USA for the evaluation and obtained data related to teen crashes from the Highway Safety Information System (HSIS) database. The team extracted demographic and land use characteristics using two different buffer widths (0.25 miles and 0.5 miles) at each selected road segment, with the number of crashes on each road segment used as the dependent variable. The generalized linear models with negative binomial distribution (GLM-based NB model) as well as the geographically weighted negative binomial regression (GWNBR) and geographically weighted negative binomial regression model with global dispersion (GWNBRg) were developed and compared. This research relied on data for 147 geographically distributed road segments for modeling and data for 49 segments for validation. The annual average daily traffic (AADT), light commercial land use, light industrial land use, number of household units, and number of pupils enrolled in public or private high schools are significant explanatory variables influencing the teen crash frequency. Both methods have good predictive capabilities and can be used to estimate the teen crash frequency. However, the GWNBR and GWNBRg better capture the spatial dependency and spatial heterogeneity among road teen crashes and the associated risk factors.
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Kim, Changmo, Ghazan Khan, Brent Nguyen i Emily L. Hoang. Development of a Statistical Model to Predict Materials’ Unit Prices for Future Maintenance and Rehabilitation in Highway Life Cycle Cost Analysis. Mineta Transportation Institute, grudzień 2020. http://dx.doi.org/10.31979/mti.2020.1806.

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The main objectives of this study are to investigate the trends in primary pavement materials’ unit price over time and to develop statistical models and guidelines for using predictive unit prices of pavement materials instead of uniform unit prices in life cycle cost analysis (LCCA) for future maintenance and rehabilitation (M&R) projects. Various socio-economic data were collected for the past 20 years (1997–2018) in California, including oil price, population, government expenditure in transportation, vehicle registration, and other key variables, in order to identify factors affecting pavement materials’ unit price. Additionally, the unit price records of the popular pavement materials were categorized by project size (small, medium, large, and extra-large). The critical variables were chosen after identifying their correlations, and the future values of each variable were predicted through time-series analysis. Multiple regression models using selected socio-economic variables were developed to predict the future values of pavement materials’ unit price. A case study was used to compare the results between the uniform unit prices in the current LCCA procedures and the unit prices predicted in this study. In LCCA, long-term prediction involves uncertainties due to unexpected economic trends and industrial demand and supply conditions. Economic recessions and a global pandemic are examples of unexpected events which can have a significant influence on variations in material unit prices and project costs. Nevertheless, the data-driven scientific approach as described in this research reduces risk caused by such uncertainties and enables reasonable predictions for the future. The statistical models developed to predict the future unit prices of the pavement materials through this research can be implemented to enhance the current LCCA procedure and predict more realistic unit prices and project costs for the future M&R activities, thus promoting the most cost-effective alternative in LCCA.
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Wideman, Jr., Robert F., Nicholas B. Anthony, Avigdor Cahaner, Alan Shlosberg, Michel Bellaiche i William B. Roush. Integrated Approach to Evaluating Inherited Predictors of Resistance to Pulmonary Hypertension Syndrome (Ascites) in Fast Growing Broiler Chickens. United States Department of Agriculture, grudzień 2000. http://dx.doi.org/10.32747/2000.7575287.bard.

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Background PHS (pulmonary hypertension syndrome, ascites syndrome) is a serious cause of loss in the broiler industry, and is a prime example of an undesirable side effect of successful genetic development that may be deleteriously manifested by factors in the environment of growing broilers. Basically, continuous and pinpointed selection for rapid growth in broilers has led to higher oxygen demand and consequently to more frequent manifestation of an inherent potential cardiopulmonary incapability to sufficiently oxygenate the arterial blood. The multifaceted causes and modifiers of PHS make research into finding solutions to the syndrome a complex and multi threaded challenge. This research used several directions to better understand the development of PHS and to probe possible means of achieving a goal of monitoring and increasing resistance to the syndrome. Research Objectives (1) To evaluate the growth dynamics of individuals within breeding stocks and their correlation with individual susceptibility or resistance to PHS; (2) To compile data on diagnostic indices found in this work to be predictive for PHS, during exposure to experimental protocols known to trigger PHS; (3) To conduct detailed physiological evaluations of cardiopulmonary function in broilers; (4) To compile data on growth dynamics and other diagnostic indices in existing lines selected for susceptibility or resistance to PHS; (5) To integrate growth dynamics and other diagnostic data within appropriate statistical procedures to provide geneticists with predictive indices that characterize resistance or susceptibility to PHS. Revisions In the first year, the US team acquired the costly Peckode weigh platform / individual bird I.D. system that was to provide the continuous (several times each day), automated weighing of birds, for a comprehensive monitoring of growth dynamics. However, data generated were found to be inaccurate and irreproducible, so making its use implausible. Henceforth, weighing was manual, this highly labor intensive work precluding some of the original objectives of using such a strategy of growth dynamics in selection procedures involving thousands of birds. Major conclusions, solutions, achievements 1. Healthy broilers were found to have greater oscillations in growth velocity and acceleration than PHS susceptible birds. This proved the scientific validity of our original hypothesis that such differences occur. 2. Growth rate in the first week is higher in PHS-susceptible than in PHS-resistant chicks. Artificial neural network accurately distinguished differences between the two groups based on growth patterns in this period. 3. In the US, the unilateral pulmonary occlusion technique was used in collaboration with a major broiler breeding company to create a commercial broiler line that is highly resistant to PHS induced by fast growth and low ambient temperatures. 4. In Israel, lines were obtained by genetic selection on PHS mortality after cold exposure in a dam-line population comprising of 85 sire families. The wide range of PHS incidence per family (0-50%), high heritability (about 0.6), and the results in cold challenged progeny, suggested a highly effective and relatively easy means for selection for PHS resistance 5. The best minimally-invasive diagnostic indices for prediction of PHS resistance were found to be oximetry, hematocrit values, heart rate and electrocardiographic (ECG) lead II waves. Some differences in results were found between the US and Israeli teams, probably reflecting genetic differences in the broiler strains used in the two countries. For instance the US team found the S wave amplitude to predict PHS susceptibility well, whereas the Israeli team found the P wave amplitude to be a better valid predictor. 6. Comprehensive physiological studies further increased knowledge on the development of PHS cardiopulmonary characteristics of pre-ascitic birds, pulmonary arterial wedge pressures, hypotension/kidney response, pulmonary hemodynamic responses to vasoactive mediators were all examined in depth. Implications, scientific and agricultural Substantial progress has been made in understanding the genetic and environmental factors involved in PHS, and their interaction. The two teams each successfully developed different selection programs, by surgical means and by divergent selection under cold challenge. Monitoring of the progress and success of the programs was done be using the in-depth estimations that this research engendered on the reliability and value of non-invasive predictive parameters. These findings helped corroborate the validity of practical means to improve PHT resistance by research-based programs of selection.
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Li, Ming. Meta-analysis of factors predicting Kawasaki disease shock syndrome. INPLASY - International Platform of Registered Systematic Review Protocols, kwiecień 2020. http://dx.doi.org/10.37766/inplasy2020.4.0045.

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