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The use of artificial intelligence (AI) in medical decision-making has the potential to revolutionize healthcare by improving the accuracy and efficiency of clinical decision-making. AI-driven decision support systems (AI-DSS) can help physicians analyze data and facilitate the search for a correct diagnosis or suitable intervention. However, the implementation of AI in clinical practice is not without challenges. Physicians' perceptions of AI-DSS are crucial to the successful implementation of these systems. Physicians describe a need to incorporate AI-DSS into existing decision-making processes, and they want more information and further influence on the system. Recent studies in the clinical decision support system area demonstrate a prevalence of data-driven AI, which can be adopted autonomously in purely data-driven systems or in cooperation with domain knowledge in hybrid systems. The effective design and use of AI tools in healthcare and medicine require the contribution of the medical decision-making research community. The context, setting, data, role of uncertainty, and human interaction with the information are key factors for realizing success. Therefore, there is a substantial role for the medical decision-making research community to contribute to the effective design and use of AI tools in healthcare and medicine. |
