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

Viewpoints on and Experiences with Digital Technologies in Health (99) Artificial Intelligence (2129) Decision Support for Health Professionals (1539) Machine Learning (2076) Clinical Information and Decision Making (1915)

Published on in Vol 9, No 5 (2021): May

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/27778, first published .
A Roadmap for Automating Lineage Tracing to Aid Automatically Explaining Machine Learning Predictions for Clinical Decision Support

A Roadmap for Automating Lineage Tracing to Aid Automatically Explaining Machine Learning Predictions for Clinical Decision Support

A Roadmap for Automating Lineage Tracing to Aid Automatically Explaining Machine Learning Predictions for Clinical Decision Support

Authors of this article:

Gang Luo1 Author Orcid Image
Article Authors Cited by (4) Tweetations (1) Metrics

Journals

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  2. Xiao N, Huang X, Wu Y, Li B, Zang W, Shinwari K, Tuzankina I, Chereshnev V, Liu G. Opportunities and challenges with artificial intelligence in allergy and immunology: a bibliometric study. Frontiers in Medicine 2025;12 View
  3. Geng S, Wang J, Xia Y, Niu B, Deng X, Wu X. Predicting generalized anxiety disorder among Chinese depressed adolescents: an explainable machine learning approach. BMC Medical Informatics and Decision Making 2025;25(1) View

Books/Policy Documents

  1. Kalina J. Diverse Perspectives and State-of-the-Art Approaches to the Utilization of Data-Driven Clinical Decision Support Systems. View