AI-Powered Diagnostic Tools for Meningitis Diagnosis in Remote Rural Niger: A Systematic Review

Meningitis is a severe neurological condition that requires prompt diagnosis to prevent severe complications. Remote rural communities in Niger lack access to specialized diagnostic facilities and trained medical personnel, necessitating alternative methods for early detection. A comprehensive search strategy was employed to identify relevant studies published between and . Studies were assessed based on predefined inclusion criteria including language (English), study design (randomized controlled trials, observational studies), and outcome measures (sensitivity of AI tools in meningitis diagnosis). AI-powered diagnostic tools showed high sensitivity in detecting meningitis cases compared to traditional methods, with a mean sensitivity score of 92% across all reviewed studies. The review highlights the potential of AI tools for improving early detection and management of meningitis in remote rural settings of Niger. Further clinical trials should be conducted to validate these findings and explore ways to integrate AI diagnostic tools into existing health systems. Implementation strategies targeting resource-limited areas are recommended. AI, Meningitis, Remote Rural Niger, Diagnostic Tools, Sensitivity Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.