The review papers collectively explore the integration of artificial intelligence (AI) in various medical domains, including disease diagnosis, treatment, and healthcare management. AI techniques such as deep learning, machine learning, and natural language processing have significantly improved accuracy in detecting cancers, cardiovascular diseases, neurological disorders, and lung conditions. Applications extend to radiology, precision medicine, predictive analytics, and medical education, where AI enhances learning and decision-making. Ethical concerns, data biases, privacy issues, and the need for regulatory frameworks are recurring challenges that must be addressed for AI’s successful adoption in clinical practice. Studies also highlight AI's role in healthcare automation, personalized treatment, and virtual simulations for training medical professionals. While AI has shown great potential in improving healthcare efficiency, explainability and human oversight remain crucial for ensuring ethical and equitable patient care.
Goldi Soni (Tue,) studied this question.
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