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

Non-Randomized Study Protocols and Methods (Non-eHealth) (578) Artificial Intelligence (1409) Pulmonology, COPD (145) mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1424) Clinical Information and Decision Making (1426) Chronic Conditions (278) Machine Learning (1491) Voice Assistants (45) AI Applications in Biomedical Engineering (8)

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 (1) Tweetations (4) Metrics
All Time | Last Month | Last Six Months | Last Year
There are currently no tweets available for this article within the specified range.