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Artificial Intelligence in Cutaneous Leishmaniasis Diagnosis: Current Developments and Future Perspectives.

Hasnaa Talimi1,2, Kawtar Retmi3, Rachida Fissoune2

  • 1Laboratory of Parasitology and Vector-Borne-Diseases, Institut Pasteur du Maroc, Casablanca 20360, Morocco.

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|May 11, 2024
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Summary

Artificial Intelligence (AI) shows promise for diagnosing Cutaneous Leishmaniasis (CL), a global health challenge. Further research is needed to address identified gaps and develop robust AI systems for improved CL detection in endemic areas.

Keywords:
artificial intelligencecutaneous leishmaniasisdiagnosis

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Area of Science:

  • Dermatology
  • Medical Diagnostics
  • Artificial Intelligence

Background:

  • Cutaneous Leishmaniasis (CL) presents significant diagnostic challenges, especially in resource-limited regions.
  • Artificial Intelligence (AI) integration offers potential advancements in medical diagnostics, including dermatology.

Purpose of the Study:

  • To systematically review the application of AI for Cutaneous Leishmaniasis (CL) diagnosis.
  • To identify AI algorithms used for CL diagnosis and highlight research gaps.

Main Methods:

  • Systematic review of studies employing AI for CL diagnosis.
  • Analysis of AI algorithms and identified research gaps.

Main Results:

  • A limited number of studies currently utilize AI for CL diagnosis.
  • Seven key gaps were identified within the existing research.

Conclusions:

  • Addressing identified research gaps is crucial for developing effective AI diagnostic systems for CL.
  • Further research in AI for CL detection can improve diagnostic accuracy and patient outcomes in endemic regions.