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Enabling the clinical application of artificial intelligence in genomics: a perspective of the AMIA Genomics and Translational Bioinformatics Workgroup.
Walton, Nephi A; Nagarajan, Radha; Wang, Chen; Sincan, Murat; Freimuth, Robert R; Everman, David B; Walton, Derek C; McGrath, Scott P; Lemas, Dominick J; Benos, Panayiotis V; Alekseyenko, Alexander V; Song, Qianqian; Gamsiz Uzun, Ece; Taylor, Casey Overby; Uzun, Alper; Person, Thomas Nate; Rappoport, Nadav; Zhao, Zhongming; Williams, Marc S.
Afiliação
  • Walton NA; Division of Medical Genetics, University of Utah School of Medicine, Salt Lake City, UT 84112 ,United States.
  • Nagarajan R; Enterprise Information Services, Cedars-Sinai Medical Center, Los Angeles, CA 90025, United States.
  • Wang C; Information Services Department, Children's Hospital of Orange County, Orange, CA 92868, United States.
  • Sincan M; Division of Computational Biology, Department of Quantitative Health Sciences, Center for Individualized Medicine, Mayo Clinic, Rochester, MN 55905, United States.
  • Freimuth RR; Flatiron Health, New York, NY 10013, United States.
  • Everman DB; Department of Internal Medicine, Sanford School of Medicine, University of South Dakota, Sioux Falls, SD 57107, United States.
  • Walton DC; Department of Artificial Intelligence and Informatics, Center for Individualized Medicine, Mayo Clinic, Rochester, MN 55905, United States.
  • McGrath SP; EverMed Genetics and Genomics Consulting LLC, Greenville, SC 29607, United States.
  • Lemas DJ; Walton Legal PLLC, Murray, UT 84123, United States.
  • Benos PV; CITRIS Health, CITRIS and Banatao Institute, University of California Berkeley, Berkeley, CA 94720, United States.
  • Alekseyenko AV; Department of Health Outcomes and Biomedical Informatics, University of Florida, Gainesville, FL 32610, United States.
  • Song Q; Department of Epidemiology, University of Florida, Gainesville, FL 32610, United States.
  • Gamsiz Uzun E; Department of Public Health Sciences, Biomedical Informatics Center, Medical University of South Carolina, Charleston, SC 29403, United States.
  • Taylor CO; Department of Health Outcomes and Biomedical Informatics, University of Florida, Gainesville, FL 32610, United States.
  • Uzun A; Department of Pathology and Laboratory Medicine, Rhode Island Hospital and Lifespan Medical Center, Providence, RI 02915, United States.
  • Person TN; Department of Pathology and Laboratory Medicine, Warren Alpert Medical School of Brown University, Providence, RI 02915, United States.
  • Rappoport N; Departments of Medicine and Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, MD 21205, United States.
  • Zhao Z; Department of Pathology and Laboratory Medicine, Warren Alpert Medical School of Brown University, Providence, RI 02915, United States.
  • Williams MS; Legorreta Cancer Center, Brown University, Providence, RI 02915, United States.
J Am Med Inform Assoc ; 31(2): 536-541, 2024 Jan 18.
Article em En | MEDLINE | ID: mdl-38037121
ABSTRACT

OBJECTIVE:

Given the importance AI in genomics and its potential impact on human health, the American Medical Informatics Association-Genomics and Translational Biomedical Informatics (GenTBI) Workgroup developed this assessment of factors that can further enable the clinical application of AI in this space. PROCESS A list of relevant factors was developed through GenTBI workgroup discussions in multiple in-person and online meetings, along with review of pertinent publications. This list was then summarized and reviewed to achieve consensus among the group members.

CONCLUSIONS:

Substantial informatics research and development are needed to fully realize the clinical potential of such technologies. The development of larger datasets is crucial to emulating the success AI is achieving in other domains. It is important that AI methods do not exacerbate existing socio-economic, racial, and ethnic disparities. Genomic data standards are critical to effectively scale such technologies across institutions. With so much uncertainty, complexity and novelty in genomics and medicine, and with an evolving regulatory environment, the current focus should be on using these technologies in an interface with clinicians that emphasizes the value each brings to clinical decision-making.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Contexto em Saúde: 1_ASSA2030 Problema de saúde: 1_desigualdade_iniquidade Assunto principal: Inteligência Artificial / Medicina Limite: Humans Idioma: En Revista: J Am Med Inform Assoc Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Contexto em Saúde: 1_ASSA2030 Problema de saúde: 1_desigualdade_iniquidade Assunto principal: Inteligência Artificial / Medicina Limite: Humans Idioma: En Revista: J Am Med Inform Assoc Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos
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