Blood parasites such as leishmaniasis, malaria, and trypanosomiasis continue to affect vulnerable
populations worldwide. By using AI programmer develops as an innovative tool that has the
potential to develop diagnosis, treatment, prevention, control, and the prediction of parasitic disease
outbreaks, vector control, mobile health, epidemic detection, predictive modeling, disease
burden estimation in endemic areas, and understanding transmission patterns. The revolution in
the previously mentioned items helps improve patient health and provide early warnings, enabling
healthcare authorities to implement preventive measures and allocate resources efficiently.
AI expedites drug discovery in treating parasites by analyzing large datasets, predicting drug efficacy
and safety profiles, streamlining drug development, and optimizing drug formulation and
delivery methods. This reduces time and cost for production of more effective parasitic medications,
and aids in repurposing existing drugs with transformative impacts on the healthcare sector.
However, AI's potential in the field of medical parasitology is limited by complex parasite
life cycles, heterogeneity, and specialized knowledge needs, while lack of data and ethical issues
restrict its implementation. Therefore, obstacles need to be solved to efficiently realize AI's potential
in real applications. With more research and cooperation in this field, we can develop creative
techniques to combat parasitic infections and obtain a deeper understanding of them