Application and Thinking of Artificial Intelligence in General Practitioner Training

Corresponding author: Dong Kun, dongkun426@hotmail.com

DOI: 10.12201/bmr.202305.00011

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  Abstract: Purpose and Significance While AI technology has achieved fruitful results, its application in diagnosis and treatment of difficult diseases has encountered bottlenecks due to reliability, interpretability, and other issues. Methods/Processes Based on the analysis of the current situation of the application of AI technology in the medical field, this paper discusses three possible directions for the in-depth application of AI in the field of general medicine, namely, the knowledge recommendation and training of general practitioners diagnosis and treatment (GPDT) based on knowledge graph, the training of GPDT based on human-computer dialogue, and the online risk warning of GPDT based on connotation quality control technology. Results/ConclusionsFinally, this paper concludes the challenges faced for such applications and their solutions. It is expected to provide a useful guide for community hospital management decision-making and artificial intelligence research topics selection.

  Key words: Application and Thinking of Artificial Intelligence in General Practitioner Training

  Submit time: 17 May 2023

  Copyright: The copyright holder for this preprint is the author/funder, who has granted biomedRxiv a license to display the preprint in perpetuity.
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