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

General Articles on Innovation and Technology in Public Health (72) Machine Learning (1479) Cancer Survivorship (259) Breast Cancer (210) Artificial Intelligence (1390) Cancer Prognosis Models and Machine Learning (14) Innovations and Technology in Cancer Research (33)

Published on in Vol 8, No 12 (2022): December

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/35750, first published .
An Assessment of the Predictive Performance of Current Machine Learning–Based Breast Cancer Risk Prediction Models: Systematic Review

An Assessment of the Predictive Performance of Current Machine Learning–Based Breast Cancer Risk Prediction Models: Systematic Review

An Assessment of the Predictive Performance of Current Machine Learning–Based Breast Cancer Risk Prediction Models: Systematic Review

Authors of this article:

Ying Gao1 Author Orcid Image ;   Shu Li2 Author Orcid Image ;   Yujing Jin1 Author Orcid Image ;   Lengxiao Zhou1 Author Orcid Image ;   Shaomei Sun1 Author Orcid Image ;   Xiaoqian Xu1 Author Orcid Image ;   Shuqian Li1 Author Orcid Image ;   Hongxi Yang3 Author Orcid Image ;   Qing Zhang1 Author Orcid Image ;   Yaogang Wang4 Author Orcid Image
Article Authors Cited by (6) Tweetations (4) Metrics

Journals

  1. Jiang J, Chao W, Culp S, Krishna S. Artificial Intelligence in the Diagnosis and Treatment of Pancreatic Cystic Lesions and Adenocarcinoma. Cancers 2023;15(9):2410 View
  2. Mertens E, Barrenechea-Pulache A, Sagastume D, Vasquez M, Vandevijvere S, Peñalvo J. Understanding the contribution of lifestyle in breast cancer risk prediction: a systematic review of models applicable to Europe. BMC Cancer 2023;23(1) View
  3. Lowry K, Zuiderveld C. Artificial Intelligence for Breast Cancer Risk Assessment. Radiologic Clinics of North America 2024;62(4):619 View
  4. Bu Z, Jiang N, Li K, Lu Z, Zhang N, Yan S, Chen Z, Hao Y, Zhang Y, Xu R, Chi H, Chen Z, Liu J, Wang D, Xu F, Liu Z. Development and Validation of an Interpretable Machine Learning Model for Early Prognosis Prediction in ICU Patients with Malignant Tumors and Hyperkalemia. Medicine 2024;103(30):e38747 View
  5. Ramezani Z, Charati J, Alizadeh-Navaei R, Eslamijouybari M. Accelerated hazard prediction based on age time-scale for women diagnosed with breast cancer using a deep learning method. BMC Medical Informatics and Decision Making 2024;24(1) View

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  1. Yadav R, Rawat R, Jha S, Rahul M, Yadav V. Innovative Computing and Communications. View