This paper is in the following e-collection/theme issue:

Digital Health Reviews (1727) Precision Medicine (160) Clinical Information and Decision Making (1919) Machine Learning (2078) Formative Evaluation of Digital Health Interventions (3237)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/48527, first published .
Predictive Value of Machine Learning for Platinum Chemotherapy Responses in Ovarian Cancer: Systematic Review and Meta-Analysis

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

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

Authors of this article:

Qingyi Wang1 Author Orcid Image ;   Zhuo Chang2 Author Orcid Image ;   Xiaofang Liu1 Author Orcid Image ;   Yunrui Wang1 Author Orcid Image ;   Chuwen Feng1 Author Orcid Image ;   Yunlu Ping1 Author Orcid Image ;   Xiaoling Feng3 Author Orcid Image
Article Authors Cited by (9) Tweetations (5) Metrics

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  6. Abdul Rasool Hassan B, Mohammed A, Hallit S, Malaeb D, Hosseini H. Exploring the role of artificial intelligence in chemotherapy development, cancer diagnosis, and treatment: present achievements and future outlook. Frontiers in Oncology 2025;15 View
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  8. Zeng X, Li Z, Dai L, Li J, Liao L, Chen W. Machine learning in ovarian cancer: a bibliometric and visual analysis from 2004 to 2024. Discover Oncology 2025;16(1) View
  9. Huang M, Law H, Tam S. Use of Radiomics in Characterizing Tumor Hypoxia. International Journal of Molecular Sciences 2025;26(14):6679 View