Predictive Value of Machine Learning for Platinum Chemotherapy Responses in Ovarian Cancer: Systematic Review and Meta-Analysis

• Published in: Journal of medical Internet research Vol. 26; no. 8; p. e48527
• Main Authors: Wang, Qingyi, Chang, Zhuo, Liu, Xiaofang, Wang, Yunrui, Feng, Chuwen, Ping, Yunlu, Feng, Xiaoling
• Format: Journal Article
• Language: English
• Published: Canada Journal of Medical Internet Research 22.01.2024; Gunther Eysenbach MD MPH, Associate Professor; JMIR Publications
• Subjects: Accuracy; Bias; Cancer; Cancer therapies; Chemotherapy; Databases, Factual; Decision making; DNA methylation; Female; Humans; Literature reviews; Machine Learning; Medical prognosis; Medical research; Meta-analysis; Mortality; Multimedia; Oncology, Experimental; Ovarian cancer; Ovarian Neoplasms - drug therapy; Patients; Prediction models; PubMed; Review; Risk assessment; Subject heading schemes; Support Vector Machine; Systematic review; Variables; machine learning; ovarian cancer; predictive potential; platinum chemotherapy response; platinum-based therapy

Machine learning is a potentially effective method for predicting the response to platinum-based treatment for ovarian cancer. However, the predictive performance of various machine learning methods and variables is still a matter of controversy and debate. This study aims to systematically review r...