AI For Medical Diagnosis: Advances, Applications, And Future Directions

Abstract

AI (Artificial Intelligence) is significantly advancing clinical diagnostic processes. Recent progress in the use of AI for medical diagnostics, such as computer vision based on medical imaging and understanding physiological signs and symptoms (acoustic cardiac signals), is discussed in this review paper. A literature review was conducted covering the period 2016-2025, and the results of this research are presented, examining the achievements of AI systems, the issues encountered in the diagnostic process, and their ethical implications. From the results presented thus far, AI matches specialists on narrow, well-defined imaging tasks; approaches non-expert level for open-ended generative diagnosis; and still trails experts overall. One crucial and undeniable task of explainable AI (XAI) is to build trust in these systems among clinicians. Finally, some promising pilots of clinical engagement and research priorities are presented, along with the possibilities (and restrictions) of the capabilities that AI can bring to this field.