Machine-learning-based artificial intelligence tools for the diagnosis of tropical fevers: a systematic review and meta-analysis protocol of diagnostic test accuracy.

ABSTRACT: Recent advancements in diagnosing tropical fevers increasingly use artificial intelligence (AI). These innovations focus on diagnosing single or multiple diseases, significantly reducing the global burden of tropical fevers. This protocol helps to identify the key factors required for a systematic review of AI-based machine learning (ML) diagnostic test accuracy-based studies to obtain a view on the pooled performance of different types of available tools. This systematic review protocol aims to review the type of ML-based AI tools and pool the performance metrics of the currently available ML-based AI devices. Patients with tropical fevers will be recruited, whereas the ML-based AI model will be the index test, and dengue, scrub typhus, leptospirosis, malaria, influenza, typhoid, chikungu

SUBMITTER: Chitrapady S 

PROVIDER: S-EPMC12382579 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature