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Manish Jain
Keywords:
Artificial Intelligence, Machine Learning, Deep Learning, Smart Healthcare, Diagnostics, Medical Imaging, Explainable AI.
Abstract:
Artificial Intelligence (AI) has emerged as a transformative technology in healthcare, enabling rapid, accurate, and cost-effective diagnostic solutions. AI models, particularly machine learning (ML) and deep learning (DL), have significantly improved disease detection, medical image analysis, predictive analytics, and clinical decision-making. The integration of AI into smart healthcare systems has enhanced diagnostic precision while reducing human errors and healthcare costs. This review provides an analytical assessment of AI models used in smart healthcare diagnostics, discussing their methodologies, performance metrics, applications, advantages, limitations, ethical concerns, and future prospects. The article compares traditional machine learning techniques with advanced deep learning architectures and explores explainable AI, federated learning, and multimodal AI as emerging trends. The review concludes that AI-driven diagnostics have the potential to revolutionize healthcare delivery, although challenges related to data privacy, interpretability, bias, and regulatory compliance must be addressed for successful clinical implementation.
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International Journal of Recent Research and Review
ISSN: 2277-8322
Vol. XIX, Issue 3
August 2026
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PUBLISHED
August 2026
ISSUE
Vol. XIX, Issue 3
SECTION
Articles
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