A Game-changing AI tool to detect and track Leprosy through fingerprint infrared scans – Affordable and revolutionary disease diagnosis

This study presents an innovative, low-cost diagnostic solution for leprosy using
AI-powered analysis of fingerprint infrared scans. The tool leverages thermal imaging
and machine learning algorithms to detect physiological patterns linked to leprosy-related nerve
damage — enabling early, non-invasive, and scalable screening, particularly in remote or
underserved regions.

Developed as part of a broader initiative for neglected tropical disease diagnostics,
this solution has the potential to revolutionize how leprosy is tracked and managed in endemic areas,
addressing both public health and social stigma through accessible technology.

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Dr. Alexandre de Fátima Cobre, a Mozambican scientist affiliated with The University of Manchester (UK), specialist in AI applied to drug discovery, collaborator of the WHO, and founder of MozBioMed.AI.

  • Ranked among the Top 3 Pharmaceutical Scientists in Brazil (2025)
  • Author of over 50 international publications
  • Recognized for pioneering AI-based discoveries in COVID-19

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