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Artificial Intelligence Algorithms for Expert Identification in Medical Domains: A Scoping Review.
Borna, Sahar; Barry, Barbara A; Makarova, Svetlana; Parte, Yogesh; Haider, Clifton R; Sehgal, Ajai; Leibovich, Bradley C; Forte, Antonio Jorge.
Afiliação
  • Borna S; Division of Plastic Surgery, Mayo Clinic, Jacksonville, FL 32224, USA.
  • Barry BA; Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN 55905, USA.
  • Makarova S; Center for Digital Health, Mayo Clinic, Rochester, MN 55905, USA.
  • Parte Y; Center for Digital Health, Mayo Clinic, Rochester, MN 55905, USA.
  • Haider CR; Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, MN 55905, USA.
  • Sehgal A; Center for Digital Health, Mayo Clinic, Rochester, MN 55905, USA.
  • Leibovich BC; Center for Digital Health, Mayo Clinic, Rochester, MN 55905, USA.
  • Forte AJ; Department of Urology, Mayo Clinic, Rochester, MN 55905, USA.
Eur J Investig Health Psychol Educ ; 14(5): 1182-1196, 2024 Apr 28.
Article em En | MEDLINE | ID: mdl-38785576
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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Eur J Investig Health Psychol Educ Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Eur J Investig Health Psychol Educ Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos