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Medical diagnosis is a fundamental aspect of effective healthcare, requiring precision and efficiency to guide treatment decisions. This paper reviews the evolution of medical diagnostic systems, from traditional methods to the integration of Artificial Intelligence (AI). It discusses the limitations of conventional approaches, particularly in handling complex medical data, and explores the transformative impact of AI through machine learning, deep learning, and natural language processing. The paper examines AI applications in disease detection, comparing them to traditional methods, and highlights key advancements in the field. It concludes by addressing the benefits, challenges, and potential future directions for AI in healthcare.

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Review of Medical Diagnosis Systems: From Traditional Techniques to Advanced AI Models

  • 会议论文

  • 发表日期：

    2026年

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  • Abir Maali,
  • Achraf Berrajaa,
  • El Arbi Abdellaoui Alaoui,
  • Mostafa Merras

摘要

Medical diagnosis is a fundamental aspect of effective healthcare, requiring precision and efficiency to guide treatment decisions. This paper reviews the evolution of medical diagnostic systems, from traditional methods to the integration of Artificial Intelligence (AI). It discusses the limitations of conventional approaches, particularly in handling complex medical data, and explores the transformative impact of AI through machine learning, deep learning, and natural language processing. The paper examines AI applications in disease detection, comparing them to traditional methods, and highlights key advancements in the field. It concludes by addressing the benefits, challenges, and potential future directions for AI in healthcare.