Artigos de revistas sobre o tema "Radiomics analysis"
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Hu, Shuyi, Xiajie Lyu, Weifeng Li, Xiaohan Cui, Qiaoyu Liu, Xiaoliang Xu, Jincheng Wang, Lin Chen, Xudong Zhang e Yin Yin. "Radiomics Analysis on Noncontrast CT for Distinguishing Hepatic Hemangioma (HH) and Hepatocellular Carcinoma (HCC)". Contrast Media & Molecular Imaging 2022 (25 de junho de 2022): 1–8. http://dx.doi.org/10.1155/2022/7693631.
Texto completo da fonteYin, Yunchao, Derya Yakar, Rudi A. J. O. Dierckx, Kim B. Mouridsen, Thomas C. Kwee e Robbert J. de Haas. "Combining Hepatic and Splenic CT Radiomic Features Improves Radiomic Analysis Performance for Liver Fibrosis Staging". Diagnostics 12, n.º 2 (21 de fevereiro de 2022): 550. http://dx.doi.org/10.3390/diagnostics12020550.
Texto completo da fonteGelardi, Fabrizia, Lara Cavinato, Rita De Sanctis, Gaia Ninatti, Paola Tiberio, Marcello Rodari, Alberto Zambelli et al. "The Predictive Role of Radiomics in Breast Cancer Patients Imaged by [18F]FDG PET: Preliminary Results from a Prospective Cohort". Diagnostics 14, n.º 20 (17 de outubro de 2024): 2312. http://dx.doi.org/10.3390/diagnostics14202312.
Texto completo da fonteCinarer, Gokalp, e Bulent Gursel Emiroglu. "Statistical analysis of radiomic features in differentiation of glioma grades". New Trends and Issues Proceedings on Advances in Pure and Applied Sciences, n.º 12 (30 de abril de 2020): 68–79. http://dx.doi.org/10.18844/gjpaas.v0i12.4988.
Texto completo da fonteChilaca-Rosas, Maria-Fatima, Melissa Garcia-Lezama, Sergio Moreno-Jimenez e Ernesto Roldan-Valadez. "Diagnostic Performance of Selected MRI-Derived Radiomics Able to Discriminate Progression-Free and Overall Survival in Patients with Midline Glioma and the H3F3AK27M Mutation". Diagnostics 13, n.º 5 (23 de fevereiro de 2023): 849. http://dx.doi.org/10.3390/diagnostics13050849.
Texto completo da fonteHu, Yumin, Qiaoyou Weng, Haihong Xia, Tao Chen, Chunli Kong, Weiyue Chen, Peipei Pang, Min Xu, Chenying Lu e Jiansong Ji. "A radiomic nomogram based on arterial phase of CT for differential diagnosis of ovarian cancer". Abdominal Radiology 46, n.º 6 (junho de 2021): 2384–92. http://dx.doi.org/10.1007/s00261-021-03120-w.
Texto completo da fonteLei, Chu-qian, Wei Wei, Zhen-yu Liu, Qian-Qian Xiong, Ci-Qiu Yang, Teng Zhu, Liu-Lu Zhang, Mei Yang, Jie Tian e Kun Wang. "Radiomics analysis for pathological classification prediction in BI-RADS category 4 mammographic calcifications." Journal of Clinical Oncology 37, n.º 15_suppl (20 de maio de 2019): e13055-e13055. http://dx.doi.org/10.1200/jco.2019.37.15_suppl.e13055.
Texto completo da fonteWei, Zhi-Yao, Zhe Zhang, Dong-Li Zhao, Wen-Ming Zhao e Yuan-Guang Meng. "Magnetic resonance imaging-based radiomics model for preoperative assessment of risk stratification in endometrial cancer". World Journal of Clinical Cases 12, n.º 26 (16 de setembro de 2024): 5908–21. http://dx.doi.org/10.12998/wjcc.v12.i26.5908.
Texto completo da fonteKalasauskas, Darius, Michael Kosterhon, Naureen Keric, Oliver Korczynski, Andrea Kronfeld, Florian Ringel, Ahmed Othman e Marc A. Brockmann. "Beyond Glioma: The Utility of Radiomic Analysis for Non-Glial Intracranial Tumors". Cancers 14, n.º 3 (7 de fevereiro de 2022): 836. http://dx.doi.org/10.3390/cancers14030836.
Texto completo da fonteHuang, Yen-Cho, Shih-Ming Huang, Jih-Hsiang Yeh, Tung-Chieh Chang, Din-Li Tsan, Chien-Yu Lin e Shu-Ju Tu. "Utility of CT Radiomics and Delta Radiomics for Survival Evaluation in Locally Advanced Nasopharyngeal Carcinoma with Concurrent Chemoradiotherapy". Diagnostics 14, n.º 9 (30 de abril de 2024): 941. http://dx.doi.org/10.3390/diagnostics14090941.
Texto completo da fonteHarrison, Rebecca, Bryce Wei Quan Tan, Hong Qi Tan, Lloyd Tan, Mei Chin Lim, Clement Yong, John Kuo e Shelli Kesler. "NIMG-32. THE PREDICTIVE CAPACITY OF PRE-OPERATIVE IMAGING ANALYSIS IN DIFFUSE GLIOMA: A COMPARISON OF CONNECTOMICS, RADIOMICS, AND CLINICAL PREDICTIVE MODELS". Neuro-Oncology 22, Supplement_2 (novembro de 2020): ii154—ii155. http://dx.doi.org/10.1093/neuonc/noaa215.645.
Texto completo da fonteChiu, Hwa-Yen, Ting-Wei Wang, Ming-Sheng Hsu, Heng-Shen Chao, Chien-Yi Liao, Chia-Feng Lu, Yu-Te Wu e Yuh-Ming Chen. "Progress in Serial Imaging for Prognostic Stratification of Lung Cancer Patients Receiving Immunotherapy: A Systematic Review and Meta-Analysis". Cancers 16, n.º 3 (31 de janeiro de 2024): 615. http://dx.doi.org/10.3390/cancers16030615.
Texto completo da fonteGangil, Tarun, Krishna Sharan, B. Dinesh Rao, Krishnamoorthy Palanisamy, Biswaroop Chakrabarti e Rajagopal Kadavigere. "Utility of adding Radiomics to clinical features in predicting the outcomes of radiotherapy for head and neck cancer using machine learning". PLOS ONE 17, n.º 12 (15 de dezembro de 2022): e0277168. http://dx.doi.org/10.1371/journal.pone.0277168.
Texto completo da fonteSun, Zongqiong, Linfang Jin, Shuai Zhang, Shaofeng Duan, Wei Xing e Shudong Hu. "Preoperative prediction for lauren type of gastric cancer: A radiomics nomogram analysis based on CT images and clinical features". Journal of X-Ray Science and Technology 29, n.º 4 (27 de julho de 2021): 675–86. http://dx.doi.org/10.3233/xst-210888.
Texto completo da fonteMiccò, Maura, Benedetta Gui, Luca Russo, Luca Boldrini, Jacopo Lenkowicz, Stefania Cicogna, Francesco Cosentino et al. "Preoperative Tumor Texture Analysis on MRI for High-Risk Disease Prediction in Endometrial Cancer: A Hypothesis-Generating Study". Journal of Personalized Medicine 12, n.º 11 (7 de novembro de 2022): 1854. http://dx.doi.org/10.3390/jpm12111854.
Texto completo da fonteWang, Yong, Liang Zhang, Lin Qi, Xiaoping Yi, Minghao Li, Mao Zhou, Danlei Chen et al. "Machine Learning: Applications and Advanced Progresses of Radiomics in Endocrine Neoplasms". Journal of Oncology 2021 (11 de outubro de 2021): 1–17. http://dx.doi.org/10.1155/2021/8615450.
Texto completo da fonteLee, Hyunjong, Seung Hwan Moon, Jung Yong Hong, Jeeyun Lee e Seung Hyup Hyun. "A Machine Learning Approach Using FDG PET-Based Radiomics for Prediction of Tumor Mutational Burden and Prognosis in Stage IV Colorectal Cancer". Cancers 15, n.º 15 (28 de julho de 2023): 3841. http://dx.doi.org/10.3390/cancers15153841.
Texto completo da fonteGill, Andrew B., Leonardo Rundo, Jonathan C. M. Wan, Doreen Lau, Jeries P. Zawaideh, Ramona Woitek, Fulvio Zaccagna et al. "Correlating Radiomic Features of Heterogeneity on CT with Circulating Tumor DNA in Metastatic Melanoma". Cancers 12, n.º 12 (24 de novembro de 2020): 3493. http://dx.doi.org/10.3390/cancers12123493.
Texto completo da fonteChilaca-Rosas, Maria-Fatima, Manuel-Tadeo Contreras-Aguilar, Melissa Garcia-Lezama, David-Rafael Salazar-Calderon, Raul-Gabriel Vargas-Del-Angel, Sergio Moreno-Jimenez, Patricia Piña-Sanchez, Raul-Rogelio Trejo-Rosales, Felipe-Alfredo Delgado-Martinez e Ernesto Roldan-Valadez. "Identification of Radiomic Signatures in Brain MRI Sequences T1 and T2 That Differentiate Tumor Regions of Midline Gliomas with H3.3K27M Mutation". Diagnostics 13, n.º 16 (14 de agosto de 2023): 2669. http://dx.doi.org/10.3390/diagnostics13162669.
Texto completo da fonteStoyanova, Radka, Olmo Zavala-Romero, Deukwoo Kwon, Adrian L. Breto, Isaac R. Xu, Ahmad Algohary, Mohammad Alhusseini et al. "Clinical-Genomic Risk Group Classification of Suspicious Lesions on Prostate Multiparametric-MRI". Cancers 15, n.º 21 (31 de outubro de 2023): 5240. http://dx.doi.org/10.3390/cancers15215240.
Texto completo da fonteLucia, François, Vincent Bourbonne, Dimitris Visvikis, Omar Miranda, Dorothy M. Gujral, Dominique Gouders, Gurvan Dissaux et al. "Radiomics Analysis of 3D Dose Distributions to Predict Toxicity of Radiotherapy for Cervical Cancer". Journal of Personalized Medicine 11, n.º 5 (11 de maio de 2021): 398. http://dx.doi.org/10.3390/jpm11050398.
Texto completo da fonteWei, JingWei, Jie Tian, Sirui Fu e Ligong Lu. "Noninvasive prediction of future macrovascular invasion occurrence in hepatocellular carcinoma based on quantitative imaging analysis: A multi-center study." Journal of Clinical Oncology 37, n.º 15_suppl (20 de maio de 2019): e14623-e14623. http://dx.doi.org/10.1200/jco.2019.37.15_suppl.e14623.
Texto completo da fonteCosta, Guido, Lara Cavinato, Chiara Masci, Francesco Fiz, Martina Sollini, Letterio Salvatore Politi, Arturo Chiti et al. "Virtual Biopsy for Diagnosis of Chemotherapy-Associated Liver Injuries and Steatohepatitis: A Combined Radiomic and Clinical Model in Patients with Colorectal Liver Metastases". Cancers 13, n.º 12 (20 de junho de 2021): 3077. http://dx.doi.org/10.3390/cancers13123077.
Texto completo da fonteBaine, Michael, Justin Burr, Qian Du, Chi Zhang, Xiaoying Liang, Luke Krajewski, Laura Zima, Gerard Rux, Chi Zhang e Dandan Zheng. "The Potential Use of Radiomics with Pre-Radiation Therapy MR Imaging in Predicting Risk of Pseudoprogression in Glioblastoma Patients". Journal of Imaging 7, n.º 2 (28 de janeiro de 2021): 17. http://dx.doi.org/10.3390/jimaging7020017.
Texto completo da fonteBioletto, Fabio, Nunzia Prencipe, Alessandro Maria Berton, Luigi Simone Aversa, Daniela Cuboni, Emanuele Varaldo, Valentina Gasco, Ezio Ghigo e Silvia Grottoli. "Radiomic Analysis in Pituitary Tumors: Current Knowledge and Future Perspectives". Journal of Clinical Medicine 13, n.º 2 (7 de janeiro de 2024): 336. http://dx.doi.org/10.3390/jcm13020336.
Texto completo da fonteSolopova, A. E., J. V. Nosova e B. B. Bendzhenova. "Magnetic resonance imaging in cervical cancer: current opportunities of radiomics analysis and prospects for its further developmen". Obstetrics, Gynecology and Reproduction 17, n.º 4 (6 de setembro de 2023): 500–511. http://dx.doi.org/10.17749/2313-7347/ob.gyn.rep.2023.440.
Texto completo da fonteZhang, Junjie, Ligang Hao, Min Li, Qian Xu e Gaofeng Shi. "CT Radiomics Combined With Clinicopathological Features to Predict Invasive Mucinous Adenocarcinoma in Patients With Lung Adenocarcinoma". Technology in Cancer Research & Treatment 22 (janeiro de 2023): 153303382311743. http://dx.doi.org/10.1177/15330338231174306.
Texto completo da fonteAbdurixiti, Meilinuer, Mayila Nijiati, Rongfang Shen, Qiu Ya, Naibijiang Abuduxiku e Mayidili Nijiati. "Current progress and quality of radiomic studies for predicting EGFR mutation in patients with non-small cell lung cancer using PET/CT images: a systematic review". British Journal of Radiology 94, n.º 1122 (1 de junho de 2021): 20201272. http://dx.doi.org/10.1259/bjr.20201272.
Texto completo da fonteSchmidt, Ian A., e Elena D. Kotina. "Applying radiomics in computed tomography data analysis to predict sarcopenia". Vestnik of Saint Petersburg University. Applied Mathematics. Computer Science. Control Processes 20, n.º 3 (2024): 376–90. http://dx.doi.org/10.21638/spbu10.2024.306.
Texto completo da fonteYounan, N., H. Douzane, A. Duran-Pena, L. Nichelli, Y. Garcilazo, C. Dehais, F. Ducray et al. "OS9.2 Radiomics analysis of lower-grade gliomas, a POLA Network study". Neuro-Oncology 21, Supplement_3 (agosto de 2019): iii18. http://dx.doi.org/10.1093/neuonc/noz126.060.
Texto completo da fonteCamastra, Chiara, Giovanni Pasini, Alessandro Stefano, Giorgio Russo, Basilio Vescio, Fabiano Bini, Franco Marinozzi e Antonio Augimeri. "Development and Implementation of an Innovative Framework for Automated Radiomics Analysis in Neuroimaging". Journal of Imaging 10, n.º 4 (22 de abril de 2024): 96. http://dx.doi.org/10.3390/jimaging10040096.
Texto completo da fonteBadesha, Arshpreet Singh, Russell Frood, Marc A. Bailey, Patrick M. Coughlin e Andrew F. Scarsbrook. "A Scoping Review of Machine-Learning Derived Radiomic Analysis of CT and PET Imaging to Investigate Atherosclerotic Cardiovascular Disease". Tomography 10, n.º 9 (3 de setembro de 2024): 1455–87. http://dx.doi.org/10.3390/tomography10090108.
Texto completo da fonteJiang, Yan-Wei, Xiong-Jie Xu, Rui Wang e Chun-Mei Chen. "Radiomics analysis based on lumbar spine CT to detect osteoporosis". European Radiology, 30 de abril de 2022. http://dx.doi.org/10.1007/s00330-022-08805-4.
Texto completo da fonteWu, Hongyu, Ban Luo, Yali Zhao, Gang Yuan, Qiuxia Wang, Ping Liu, Linhan Zhai, Wenzhi Lv e Jing Zhang. "Radiomics analysis of the optic nerve for detecting dysthyroid optic neuropathy, based on water-fat imaging". Insights into Imaging 13, n.º 1 (24 de setembro de 2022). http://dx.doi.org/10.1186/s13244-022-01292-7.
Texto completo da fonteSantinha, João, Daniel Pinto dos Santos, Fabian Laqua, Jacob J. Visser, Kevin B. W. Groot Lipman, Matthias Dietzel, Michail E. Klontzas, Renato Cuocolo, Salvatore Gitto e Tugba Akinci D’Antonoli. "ESR Essentials: radiomics—practice recommendations by the European Society of Medical Imaging Informatics". European Radiology, 25 de outubro de 2024. http://dx.doi.org/10.1007/s00330-024-11093-9.
Texto completo da fonteCai, Du, Xin Duan, Wei Wang, Ze-Ping Huang, Qiqi Zhu, Min-Er Zhong, Min-Yi Lv et al. "A Metabolism-Related Radiomics Signature for Predicting the Prognosis of Colorectal Cancer". Frontiers in Molecular Biosciences 7 (7 de janeiro de 2021). http://dx.doi.org/10.3389/fmolb.2020.613918.
Texto completo da fonteMou, Meiyan, Ruizhi Gao, Yuquan Wu, Peng Lin, Hongxia Yin, Fenghuan Chen, Fen Huang, Rong Wen, Hong Yang e Yun He. "Endoscopic Rectal Ultrasound‐Based Radiomics Analysis for the Prediction of Synchronous Liver Metastasis in Patients With Primary Rectal Cancer". Journal of Ultrasound in Medicine, 11 de novembro de 2023. http://dx.doi.org/10.1002/jum.16369.
Texto completo da fonteShaheen, Asma, Syed Talha Bukhari, Maria Nadeem, Stefano Burigat, Ulas Bagci e Hassan Mohy-ud-Din. "Overall Survival Prediction of Glioma Patients With Multiregional Radiomics". Frontiers in Neuroscience 16 (7 de julho de 2022). http://dx.doi.org/10.3389/fnins.2022.911065.
Texto completo da fonteLi, Yue, Huaibi Huo, Hui Liu, Yue Zheng, Zhaoxin Tian, Xue Jiang, Shiqi Jin et al. "Coronary CTA-based radiomic signature of pericoronary adipose tissue predict rapid plaque progression". Insights into Imaging 15, n.º 1 (20 de junho de 2024). http://dx.doi.org/10.1186/s13244-024-01731-7.
Texto completo da fonteLi, Mei hua, Long Liu, Lian Feng, Li jun Zheng, Qin mei Xu, Yin juan Zhang, Fu rong Zhang e Lin na Feng. "Prediction of cervical lymph node metastasis in solitary papillary thyroid carcinoma based on ultrasound radiomics analysis". Frontiers in Oncology 14 (25 de janeiro de 2024). http://dx.doi.org/10.3389/fonc.2024.1291767.
Texto completo da fonteYang, Qinzhu, Haofan Huang, Guizhi Zhang, Nuoqing Weng, Zhenkai Ou, Meili Sun, Huixing Luo, Xuhui Zhou, Yi Gao e Xiaobin Wu. "Contrast‐enhanced CT‐based radiomic analysis for determining the response to anti‐programmed death‐1 therapy in esophageal squamous cell carcinoma patients: A pilot study". Thoracic Cancer, 24 de setembro de 2023. http://dx.doi.org/10.1111/1759-7714.15117.
Texto completo da fonteMeng, Huan, Tian-Da Wang, Li-Yong Zhuo, Jia-Wei Hao, Lian-yu Sui, Wei Yang, Li-Li Zang, Jing-Jing Cui, Jia-Ning Wang e Xiao-Ping Yin. "Quantitative radiomics analysis of imaging features in adults and children Mycoplasma pneumonia". Frontiers in Medicine 11 (20 de maio de 2024). http://dx.doi.org/10.3389/fmed.2024.1409477.
Texto completo da fonteWu, Ting, Chen Gao, Xinjing Lou, Jun Wu, Maosheng Xu e Linyu Wu. "Predictive value of radiomic features extracted from primary lung adenocarcinoma in forecasting thoracic lymph node metastasis: a systematic review and meta-analysis". BMC Pulmonary Medicine 24, n.º 1 (18 de maio de 2024). http://dx.doi.org/10.1186/s12890-024-03020-x.
Texto completo da fonteJiang, Yan-Wei, Xiong-Jei Xu, Rui Wang e Chun-Mei Chen. "Efficacy of non-enhanced computer tomography-based radiomics for predicting hematoma expansion: A meta-analysis". Frontiers in Oncology 12 (10 de janeiro de 2023). http://dx.doi.org/10.3389/fonc.2022.973104.
Texto completo da fonteWang, Jincheng, Shengnan Tang, Jin Wu, Shanshan Xu, Qikai Sun, Zheyu Zhou, Xiaoliang Xu et al. "Radiomic features at Contrast-enhanced CT Predict Virus-driven Liver Fibrosis: A Multi-institutional Study". Clinical and Translational Gastroenterology, 27 de maio de 2024. http://dx.doi.org/10.14309/ctg.0000000000000712.
Texto completo da fontePeng, Jiao, Zhen Tang, Tao Li, Xiaoyu Pan, Lijuan Feng e Liling Long. "Contrast-enhanced computed tomography-based radiomics nomogram for predicting HER2 status in urothelial bladder carcinoma". Frontiers in Oncology 14 (14 de agosto de 2024). http://dx.doi.org/10.3389/fonc.2024.1427122.
Texto completo da fonteYang, Bin, Li Zhou, Jing Zhong, Tangfeng Lv , Ang Li, Lu Ma, Jian Zhong et al. "Combination of computed tomography imaging-based radiomics and clinicopathological characteristics for predicting the clinical benefits of immune checkpoint inhibitors in lung cancer". Respiratory Research 22, n.º 1 (28 de junho de 2021). http://dx.doi.org/10.1186/s12931-021-01780-2.
Texto completo da fonteKawahara, Daisuke, Nobuki Imano, Riku Nishioka, Kouta Ogawa, Tomoki Kimura, Taku Nakashima, Hiroshi Iwamoto, Kazunori Fujitaka, Noboru Hattori e Yasushi Nagata. "Prediction of radiation pneumonitis after definitive radiotherapy for locally advanced non-small cell lung cancer using multi-region radiomics analysis". Scientific Reports 11, n.º 1 (10 de agosto de 2021). http://dx.doi.org/10.1038/s41598-021-95643-x.
Texto completo da fonteZhang, Simiao, Juan Hou, Wenwen Xia, Zicheng Zhao, Min Xu, Shouxian Li, Chunhui Xu, Tieliang Zhang e Wenya Liu. "Value of intralesional and perilesional radiomics for predicting the bioactivity of hepatic alveolar echinococcosis". Frontiers in Oncology 14 (27 de junho de 2024). http://dx.doi.org/10.3389/fonc.2024.1389177.
Texto completo da fonteTang, Shengnan, Jin Wu, Shanshan Xu, Qi Li e Jian He. "Clinical-radiomic analysis for non-invasive prediction of liver steatosis on non-contrast CT: A pilot study". Frontiers in Genetics 14 (20 de março de 2023). http://dx.doi.org/10.3389/fgene.2023.1071085.
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