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This paper encompasses the development and evaluation of a disease diagnosis chatbot developed to help users assess their symptoms and get preliminary diagnoses. The lack of access to medical knowledge and the high costs of healthcare are the primary obstacles for the general population. Medical chatbots, specifically created for medical uses, could overcome these challenges (Smith and Doe in J Healthc Technol 12:234–245, 2021 [1]). The subsequent document delineates the expanding utilisation of artificial intelligence and machine learning within the medical domain, encompassing the chatbot’s design methodology, system architecture (shown in Fig. 6), and practical implementation. The chatbot analyses user inputs and provides pertinent medical information by combining machine learning models and rule-based algorithms.

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Analysing the Efficacy: A Critical Assessment of a Symptom Analysis and Initial Diagnosis Chatbot for Disease Detection

  • 会议论文

  • 发表日期：

    2025年

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  • Nikit Mathur,
  • Abhinav Raja Raizada,
  • R. Jeya

摘要

This paper encompasses the development and evaluation of a disease diagnosis chatbot developed to help users assess their symptoms and get preliminary diagnoses. The lack of access to medical knowledge and the high costs of healthcare are the primary obstacles for the general population. Medical chatbots, specifically created for medical uses, could overcome these challenges (Smith and Doe in J Healthc Technol 12:234–245, 2021 [1]). The subsequent document delineates the expanding utilisation of artificial intelligence and machine learning within the medical domain, encompassing the chatbot’s design methodology, system architecture (shown in Fig. 6), and practical implementation. The chatbot analyses user inputs and provides pertinent medical information by combining machine learning models and rule-based algorithms.