Enabling the clinical application of artificial intelligence in genomics: A perspective of the AMIA Genomics and Translational Bioinformatics Workgroup

Nephi A. Walton, Radha Nagarajan, Chen Wang, Murat Sincan, Robert R. Freimuth, David B. Everman, Derek C. Walton, Scott P. McGrath, Dominick J. Lemas, Panayiotis V. Benos, Alexander V. Alekseyenko, Qianqian Song, Ece Gamsiz Uzun, Casey Overby Taylor, Alper Uzun, Thomas Nate Person, Nadav Rappoport, Zhongming Zhao, Marc S. Williams

Research output: Contribution to journalReview articlepeer-review

2 Scopus citations

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.

Original languageEnglish
Pages (from-to)536-541
Number of pages6
JournalJournal of the American Medical Informatics Association
Volume31
Issue number2
DOIs
StatePublished - 1 Feb 2024
Externally publishedYes

Keywords

  • artificial intelligence
  • bioinformatics
  • clinical genomics
  • genomics
  • machine learning
  • translational bioinformatics

ASJC Scopus subject areas

  • Health Informatics

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