ARTIFICIAL INTELLIGENCE IMPLEMENTATIONS IN PARASITOLOGY: A MINI-REVIEW ARTICLE | ||||
| Journal of the Egyptian Society of Parasitology | ||||
| Article 10, Volume 54, Issue 2, August 2024, Page 249-257 PDF (695.56 K) | ||||
| DOI: 10.21608/jesp.2024.373525 | ||||
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| Authors | ||||
| GAMAL A. ABO SHEISHAA1; MOSTAFA EL SHAHAT MOSTAFA2 | ||||
| 1Departments of Parasitology, Faculties of Medicine, Al-Azhar University, Nasr City, Egypt | ||||
| 2Departments of Parasitology, Faculties of Medicine, Al-Azhar University, Damietta, Egypt | ||||
| Abstract | ||||
| 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 | ||||
| Keywords | ||||
| artificial intelligence; machine learning; health care; parasitic diseases | ||||
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