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This research explores how deep learning and artificial intelligence can transform parasitic disease diagnosis and address associated challenges.

February 13, 2026Clinical Laboratory0 citations

The Transformative Impact of Deep Learning and Artificial Intelligence on Parasitic Disease Diagnosis

MIMohamed IbrahimMilitary Technical College HAHamad H. AlanaziUmm al-Qura University EAEman Azab

Key Points

This research explores how deep learning and artificial intelligence can transform parasitic disease diagnosis and address associated challenges.
Analysis of AI and deep learning capabilities in diagnosing parasitic diseases
Identification of data and bias challenges in AI implementation
Discussion on integrating AI with portable diagnostic tools
AI and deep learning show significant potential in improving diagnostic accuracy for parasitic diseases
Addressing data and bias challenges is crucial for equitable use of AI
Integration of AI with portable diagnostics may enhance health outcomes in endemic regions

Abstract

AI, particularly DL, holds transformative potential for parasitic disease diagnosis. Overcoming data and bias challenges is essential for ethical and equitable implementation. Collaborative efforts to integrate AI with portable diagnostics can enhance global health outcomes in endemic areas.

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