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

Clinical Information and Decision Making (1315) Registered Report (516) Machine Learning (1373) Artificial Intelligence (1189)

Published on in Vol 23, No 4 (2021): April

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/24153, first published .
Generalizability of an Automatic Explanation Method for Machine Learning Prediction Results on Asthma-Related Hospital Visits in Patients With Asthma: Quantitative Analysis

Generalizability of an Automatic Explanation Method for Machine Learning Prediction Results on Asthma-Related Hospital Visits in Patients With Asthma: Quantitative Analysis

Generalizability of an Automatic Explanation Method for Machine Learning Prediction Results on Asthma-Related Hospital Visits in Patients With Asthma: Quantitative Analysis

Authors of this article:

Gang Luo1 Author Orcid Image ;   Claudia L Nau2 Author Orcid Image ;   William W Crawford3 Author Orcid Image ;   Michael Schatz2, 4 Author Orcid Image ;   Robert S Zeiger2, 4 Author Orcid Image ;   Corinna Koebnick2 Author Orcid Image
Article Authors Cited by (4) Tweetations (3) Metrics

Journals

  1. Luo G, Stone B, Sheng X, He S, Koebnick C, Nkoy F. Using Computational Methods to Improve Integrated Disease Management for Asthma and Chronic Obstructive Pulmonary Disease: Protocol for a Secondary Analysis. JMIR Research Protocols 2021;10(5):e27065 View
  2. Luo G. A Roadmap for Automating Lineage Tracing to Aid Automatically Explaining Machine Learning Predictions for Clinical Decision Support. JMIR Medical Informatics 2021;9(5):e27778 View
  3. Zhang X, Luo G. Ranking Rule-Based Automatic Explanations for Machine Learning Predictions on Asthma Hospital Encounters in Patients With Asthma: Retrospective Cohort Study. JMIR Medical Informatics 2021;9(8):e28287 View
  4. Zeng S, Arjomandi M, Luo G. Automatically Explaining Machine Learning Predictions on Severe Chronic Obstructive Pulmonary Disease Exacerbations: Retrospective Cohort Study. JMIR Medical Informatics 2022;10(2):e33043 View