PDF(Pubmed)
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.
摘要：
丰富的信息和人与人之间的相互联系，识别特定领域的知识渊博的个人对组织来说已经变得至关重要。人工智能（AI）算法已被用来评估知识并定位特定领域的专家，减轻专家剖析和识别的人工负担。然而,只有有限的研究机构探索AI算法在医学和生物医学领域的专家发现中的应用。本研究旨在对现有的有关利用AI算法进行医疗领域专家识别的文献进行范围审查。我们使用自定义搜索字符串系统地搜索了五个平台，通过其他来源确定了21项研究。该搜索涵盖了截至2023年的研究，研究资格和选择符合PRISMA2020声明。从搜索中评估了总共571项研究。在这些中，我们纳入了2014年至2020年间进行的6项符合我们审查标准的研究.四项研究使用机器学习算法作为他们的模型，而两个人使用自然语言处理。一项研究结合了两种方法。与基线算法相比，所有六项研究在专家检索方面都取得了显著成功，由各种评分指标衡量。AI提高了专家发现的准确性和有效性。然而,智能医学专家检索还需要更多的工作。
