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

New Methods (1134) Smoking Cessation (629) Machine Learning (2076) Prevention and Health Promotion (1362) Imaging Informatics (302) Environmental Health (123) Visualization in eHealth (68) Ecological Momentary Assessment (EMA) (405) Mobile Health (mhealth) (3464) Artificial Intelligence (2129)

Published on in Vol 23, No 11 (2021): November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/27875, first published .
Prediction of Smoking Risk From Repeated Sampling of Environmental Images: Model Validation

Prediction of Smoking Risk From Repeated Sampling of Environmental Images: Model Validation

Prediction of Smoking Risk From Repeated Sampling of Environmental Images: Model Validation

Authors of this article:

Matthew M Engelhard1 Author Orcid Image ;   Joshua D'Arcy1 Author Orcid Image ;   Jason A Oliver1 Author Orcid Image ;   Rachel Kozink1 Author Orcid Image ;   F Joseph McClernon1 Author Orcid Image
Article Authors Cited by (3) Tweetations (2) Metrics

Journals

  1. Walters S, Mun E, Tan Z, Luningham J, Hébert E, Oliver J, Businelle M. Development and preliminary effectiveness of a smartphone‐based, just‐in‐time adaptive intervention for adults with alcohol misuse who are experiencing homelessness. Alcoholism: Clinical and Experimental Research 2022;46(9):1732 View
  2. Zhu E, Muneer A, Zhang J, Xia Y, Li X, Zhou C, Heymach J, Wu J, Le X. Progress and challenges of artificial intelligence in lung cancer clinical translation. npj Precision Oncology 2025;9(1) View
  3. Ng Y, Cheong S, Ang W, Lau Y, Lau S. Types, functions, and mechanisms of machine learning for personalizing smoking cessation interventions: A systematic scoping review. Artificial Intelligence in Medicine 2025;170:103274 View