Artificial Intelligence Algorithms for Expert Identification in Medical Domains: A Scoping Review.

IF 3 Q1 PSYCHOLOGY, CLINICAL
Sahar Borna, Barbara A Barry, Svetlana Makarova, Yogesh Parte, Clifton R Haider, Ajai Sehgal, Bradley C Leibovich, Antonio Jorge Forte
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Abstract

With abundant information and interconnectedness among people, identifying knowledgeable individuals in specific domains has become crucial for organizations. Artificial intelligence (AI) algorithms have been employed to evaluate the knowledge and locate experts in specific areas, alleviating the manual burden of expert profiling and identification. However, there is a limited body of research exploring the application of AI algorithms for expert finding in the medical and biomedical fields. This study aims to conduct a scoping review of existing literature on utilizing AI algorithms for expert identification in medical domains. We systematically searched five platforms using a customized search string, and 21 studies were identified through other sources. The search spanned studies up to 2023, and study eligibility and selection adhered to the PRISMA 2020 statement. A total of 571 studies were assessed from the search. Out of these, we included six studies conducted between 2014 and 2020 that met our review criteria. Four studies used a machine learning algorithm as their model, while two utilized natural language processing. One study combined both approaches. All six studies demonstrated significant success in expert retrieval compared to baseline algorithms, as measured by various scoring metrics. AI enhances expert finding accuracy and effectiveness. However, more work is needed in intelligent medical expert retrieval.

用于医学领域专家鉴定的人工智能算法:范围综述。
随着信息的丰富和人与人之间的相互联系,识别特定领域的知识型人才对企业来说变得至关重要。人工智能(AI)算法已被用于评估知识和定位特定领域的专家,从而减轻了专家剖析和识别的人工负担。然而,在医学和生物医学领域探索应用人工智能算法查找专家的研究还很有限。本研究旨在对利用人工智能算法进行医学领域专家识别的现有文献进行范围性综述。我们使用自定义搜索字符串系统地搜索了五个平台,并通过其他来源确定了 21 项研究。检索时间跨度截止到 2023 年,研究资格和选择符合 PRISMA 2020 声明。此次搜索共评估了 571 项研究。其中,我们纳入了六项在 2014 年至 2020 年间进行的研究,这些研究均符合我们的审查标准。四项研究使用机器学习算法作为模型,两项研究使用自然语言处理。一项研究将这两种方法结合在一起。所有六项研究都表明,与基线算法相比,人工智能在专家检索方面取得了显著的成功,这是以各种评分指标来衡量的。人工智能提高了专家检索的准确性和有效性。不过,在智能医学专家检索方面还需要做更多的工作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
4.40
自引率
12.50%
发文量
111
审稿时长
8 weeks
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