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Non-Randomized Study Protocols and Methods (Non-eHealth) (544) Artificial Intelligence (1198) Pulmonology, COPD (125) mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1309) Clinical Information and Decision Making (1328) Chronic Conditions (216) Machine Learning (1385) Voice Assistants (42)

Published on in Vol 13 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/54388, first published .
Leveraging AI and Machine Learning to Develop and Evaluate a Contextualized User-Friendly Cough Audio Classifier for Detecting Respiratory Diseases: Protocol for a Diagnostic Study in Rural Tanzania

Leveraging AI and Machine Learning to Develop and Evaluate a Contextualized User-Friendly Cough Audio Classifier for Detecting Respiratory Diseases: Protocol for a Diagnostic Study in Rural Tanzania

Leveraging AI and Machine Learning to Develop and Evaluate a Contextualized User-Friendly Cough Audio Classifier for Detecting Respiratory Diseases: Protocol for a Diagnostic Study in Rural Tanzania

Authors of this article:

Kahabi Ganka Isangula1 Author Orcid Image ;   Rogers John Haule1 Author Orcid Image
Article Authors Cited by Tweetations (4) Metrics

Kahabi Ganka Isangula   1 , MD, MPH, PhD ;   Rogers John Haule   1 , DipCIT

1 School of Nursing and Midwifery, Aga Khan University, Dar Es Salaam, United Republic of Tanzania

Corresponding Author:

  • Kahabi Ganka Isangula, MD, MPH, PhD
  • School of Nursing and Midwifery
  • Aga Khan University
  • Salama House, 344 Urambo St
  • PO Box 125
  • Dar Es Salaam, 255
  • United Republic of Tanzania
  • Phone: 255 754030726
  • Email: kahabi.isangula@aku.edu