Reviewing Artificial Intelligence Applications in Healthcare Diagnostics: Benefits, Challenges, and Future Directions

ABSTRACT

Artificial intelligence (AI) transforms healthcare diagnostics by enabling faster, more accurate, cost-effective disease detection and treatment planning. This paper reviews AI’s applications, benefits, challenges, and future directions in diagnostics. Key application areas include diagnostic imaging, pathology, genomics, predictive analytics, and electronic health record analysis. AI enhances diagnostic accuracy, reduces errors, and facilitates personalized medicine while optimizing healthcare resources. However, significant challenges remain, including technical limitations, regulatory complexities, ethical concerns, and barriers to adoption. Addressing these challenges requires improved data quality, interdisciplinary collaboration, enhanced regulatory frameworks, and robust ethical safeguards. Future research should focus on refining algorithms, fostering global data-sharing initiatives, and ensuring equitable access to AI-driven healthcare solutions. By overcoming these obstacles, AI has the potential to revolutionize diagnostics and improve patient outcomes across diverse healthcare settings.

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