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

Non-Randomized Study Protocols and Methods (Non-eHealth) (540) HIV/AIDS/STI Prevention and Care (816) Machine Learning (1370) Behavioural Surveillance for Public Health (204) mHealth for Data Collection and Research (907) mHealth for Screening (190) Tools, Programs and Algorithms (236)

Published on in Vol 10, No 12 (2021): December

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/30304, first published .
Utility of a Machine-Guided Tool for Assessing Risk Behavior Associated With Contracting HIV in Three Sites in South Africa: Protocol for an In-Field Evaluation

Utility of a Machine-Guided Tool for Assessing Risk Behavior Associated With Contracting HIV in Three Sites in South Africa: Protocol for an In-Field Evaluation

Utility of a Machine-Guided Tool for Assessing Risk Behavior Associated With Contracting HIV in Three Sites in South Africa: Protocol for an In-Field Evaluation

Authors of this article:

Mohammed Majam1 Author Orcid Image ;   Mothepane Phatsoane1 Author Orcid Image ;   Keith Hanna2 Author Orcid Image ;   Charles Faul2 Author Orcid Image ;   Lovkesh Arora2 Author Orcid Image ;   Sarvesh Makthal2 Author Orcid Image ;   Akhil Kumar2 Author Orcid Image ;   Kashyap Jois2 Author Orcid Image ;   Samanta Tresha Lalla-Edward1 Author Orcid Image
Article Authors Cited by (2) Tweetations (3) Metrics

Journals

  1. Fieggen J, Smith E, Arora L, Segal B. The role of machine learning in HIV risk prediction. Frontiers in Reproductive Health 2022;4 View
  2. Majam M, Segal B, Fieggen J, Smith E, Hermans L, Singh L, Phatsoane M, Arora L, Lalla-Edward S. Utility of a machine-guided tool for assessing risk behaviour associated with contracting HIV in three sites in South Africa. Informatics in Medicine Unlocked 2023;37:101192 View