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This research proposes a groundbreaking method for predicting and explaining diseases by combining deep learning and natural language processing. A sophisticated deep learning model is designed to accurately identify potential illnesses based on the symptoms provided as input. Subsequently, a large language model generates comprehensive and informative text explaining the predicted diseases, considering the provided symptoms. The proposed system undergoes rigorous training and validation processes, demonstrating promising results in both disease prediction accuracy and the quality of generated explanations. This innovative approach has the potential to provide valuable support for healthcare professionals and patients by offering rapid disease insights and understandable explanations.

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Deep Learning Based AI Diagnostic Open API Architecture for Healthcare Applications

  • 会议论文

  • 发表日期：

    2025年

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  • Fadoua Haraka,
  • Smail Tigani,
  • Mohammed Ouzzif,
  • Khalid Bouragba

摘要

This research proposes a groundbreaking method for predicting and explaining diseases by combining deep learning and natural language processing. A sophisticated deep learning model is designed to accurately identify potential illnesses based on the symptoms provided as input. Subsequently, a large language model generates comprehensive and informative text explaining the predicted diseases, considering the provided symptoms. The proposed system undergoes rigorous training and validation processes, demonstrating promising results in both disease prediction accuracy and the quality of generated explanations. This innovative approach has the potential to provide valuable support for healthcare professionals and patients by offering rapid disease insights and understandable explanations.