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

Nephi A WaltonRadha NagarajanChen WangMurat SincanRobert R FreimuthDavid B EvermanDerek C WaltonScott P McGrathDominick J LemasPanayiotis V BenosAlexander V AlekseyenkoQianqian SongEce Gamsiz UzunCasey Overby TaylorAlper UzunThomas Nate PersonNadav RappoportZhong-Ming ZhaoMarc S Williams
Published in: Journal of the American Medical Informatics Association : JAMIA (2023)
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.
Keyphrases
  • artificial intelligence
  • big data
  • machine learning
  • single cell
  • deep learning
  • decision making
  • rna seq
  • electronic health record
  • transcription factor
  • palliative care
  • healthcare