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June 17, 2026BMC Infectious DiseasesOpen Access

Performance and clinical utility of image-based machine learning models for the diagnosis of neglected tropical diseases in low- and middle-income countries: a systematic review

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Authors

DIDavid Chinaecherem InnocentUniversity of Port Harcourt PAPrecious Ebube AnyakorahCenter for Clinical Care and Research in Nigeria RIRejoicing Chijindum InnocentEnugu State University of Science and Technology

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Implication

Systematic review evaluates image-based machine learning for diagnosing neglected tropical diseases, suggesting potential benefits yet highlighting implementation challenges.

Key Points

This review aims to evaluate the diagnostic performance and clinical utility of image-based machine learning models for neglected tropical diseases in low- and middle-income countries.
Conducted systematic searches across multiple databases including PubMed/MEDLINE and Scopus from 2010 to 2026.
Included studies had to be peer-reviewed and report on image-based ML models for NTD diagnosis in LMICs.
Risk of bias was assessed using QUADAS-2, and findings were narratively synthesized.
Eight studies met inclusion criteria, with microscopy-based ML models showing sensitivities and specificities above 90% for malaria and helminth infections.
Accuracy of clinical image-based models for skin NTDs was more variable.
Implementation evaluation and external validation were inconsistently reported, limiting generalizability.

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Innocent et al. (2026) studied this question.

synapsesocial.com/papers/6a323c29d50b63ecad2066bf https://doi.org/10.1186/s12879-026-13784-8

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Implication

Systematic review evaluates image-based machine learning for diagnosing neglected tropical diseases, suggesting potential benefits yet highlighting implementation challenges.

Performance and clinical utility of image-based machine learning models for the diagnosis of neglected tropical diseases in low- and middle-income countries: a systematic review

Discussion

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Implication

Key Points

Cite This Study

Performance and clinical utility of image-based machine learning models for the diagnosis of neglected tropical diseases in low- and middle-income countries: a systematic review

Discussion

Member takes

Implication

Key Points

Cite This Study

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