ArticleFamily medicine and community health2026
Evaluation of AI tool assisting primary healthcare physicians to diagnostic and treatment tasks.
Article in Family medicine and community health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
6 authors.
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Abstract
Primary healthcare (PHC) plays an important role in the healthcare system, yet the shortage of qualified primary healthcare physician (PHP) restricts the quality of diagnostic and treatment services provided by PHC institutions. The rapid development and prevalence of artificial intelligence (AI) offer a solution to this challenge. Existing research primarily focused on two themes: evaluating the performance of AI tools and investigating PHPs' attitudes and use intention to such AI. There are three main modes used to evaluate the performance of AI tools: evaluation of single AI tool, comparison across different AI tools and comparison between AI tool and physicians. Confusion metrics and examination are two types of indicators primarily used to assess these products. PHPs generally hold positive attitudes and use intentions towards AI tools. According to the technology acceptance model, influential factors of PHPs' attitudes and use intention can be categorised into usefulness and ease of use. Limitations and future research directions are also discussed in this article, which provides insights for future research and practice to improve AI tools assisting PHPs in diagnostic and treatment tasks and promote AI adoption in PHC.
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