AI or Bust: A Call for Team Science to Translate Computer Algorithms into Clinical Applications

Author: Stephani Stancil, PhD, APRN on November 11, 2021


Although a term over a half-century old, artificial intelligence (AI) has experienced a "boom" in the last decade as evidenced by an increase in funded projects, publications, and prioritization. In Clinical and Translational Science (CTS), Bernstam and colleagues highlight the role of AI in clinical and translational research and describe successes, failures, and next steps within each tier of the clinical and translational research spectrum, from pre-clinical (T1) to public health (T4). Using a multifaceted approach, the authors highlight the rise in AI-focused NIH funded projects in the past decade balanced with the opportunities that still exist to translate AI into clinical applications and improved outcomes. 

Fueled by the availability of large data sets and ever-evolving technical capability, Bernstam et al. argue that AI stands ready to catalyze a revolution in clinical and translational science. Methodologists who design algorithms, domain experts who ensure biological relevance, and informaticists who enable clinical implementation are required players in the Team Science approach that may turn the promised future of AI into a life-saving reality for patients. 

Can't wait to dig in further? Read Bernstam et alhere.

The CTS editorial team invites you to submit your translational research to CTS. Whether your work highlights original translational research that uses AI to bridge laboratory discoveries with the diagnosis and treatment of human disease or describes an innovative application of AI in clinical practice, please consider CTS for your next contribution.

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