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

Formative Evaluation of Digital Health Interventions (2300) Surveillance Systems (441) Decision Support for Health Professionals (1175)

Published on in Vol 6, No 7 (2022): July

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/36055, first published .
An Urban Population Health Observatory for Disease Causal Pathway Analysis and Decision Support: Underlying Explainable Artificial Intelligence Model

An Urban Population Health Observatory for Disease Causal Pathway Analysis and Decision Support: Underlying Explainable Artificial Intelligence Model

An Urban Population Health Observatory for Disease Causal Pathway Analysis and Decision Support: Underlying Explainable Artificial Intelligence Model

Authors of this article:

Whitney S Brakefield1, 2 Author Orcid Image ;   Nariman Ammar1, 3 Author Orcid Image ;   Arash Shaban-Nejad1 Author Orcid Image
Article Authors Cited by (5) Tweetations (4) Metrics

Journals

  1. Brakefield W, Olusanya O, Shaban-Nejad A. Association Between Neighborhood Factors and Adult Obesity in Shelby County, Tennessee: Geospatial Machine Learning Approach. JMIR Public Health and Surveillance 2022;8(8):e37039 View
  2. Ghasemi A, Hashtarkhani S, Schwartz D, Shaban‐Nejad A. Explainable artificial intelligence in breast cancer detection and risk prediction: A systematic scoping review. Cancer Innovation 2024;3(5) View

Books/Policy Documents

  1. Shaban-Nejad A, Michalowski M, Bianco S. Multimodal AI in Healthcare. View