Artificial intelligence in clinical and translational science: Successes, challenges and opportunities

Elmer V. Bernstam, Paula K. Shireman, Funda Meric-Bernstam, Meredith N. Zozus, Xiaoqian Jiang, Bradley B. Brimhall, Ashley K. Windham, Susanne Schmidt, Shyam Visweswaran, Ye Ye, Heath Goodrum, Yaobin Ling, Seemran Barapatre, Michael J. Becich

Producción científica: Review articlerevisión exhaustiva

19 Citas (Scopus)

Resumen

Artificial intelligence (AI) is transforming many domains, including finance, agriculture, defense, and biomedicine. In this paper, we focus on the role of AI in clinical and translational research (CTR), including preclinical research (T1), clinical research (T2), clinical implementation (T3), and public (or population) health (T4). Given the rapid evolution of AI in CTR, we present three complementary perspectives: (1) scoping literature review, (2) survey, and (3) analysis of federally funded projects. For each CTR phase, we addressed challenges, successes, failures, and opportunities for AI. We surveyed Clinical and Translational Science Award (CTSA) hubs regarding AI projects at their institutions. Nineteen of 63 CTSA hubs (30%) responded to the survey. The most common funding source (48.5%) was the federal government. The most common translational phase was T2 (clinical research, 40.2%). Clinicians were the intended users in 44.6% of projects and researchers in 32.3% of projects. The most common computational approaches were supervised machine learning (38.6%) and deep learning (34.2%). The number of projects steadily increased from 2012 to 2020. Finally, we analyzed 2604 AI projects at CTSA hubs using the National Institutes of Health Research Portfolio Online Reporting Tools (RePORTER) database for 2011–2019. We mapped available abstracts to medical subject headings and found that nervous system (16.3%) and mental disorders (16.2) were the most common topics addressed. From a computational perspective, big data (32.3%) and deep learning (30.0%) were most common. This work represents a snapshot in time of the role of AI in the CTSA program.

Idioma originalEnglish (US)
Páginas (desde-hasta)309-321
Número de páginas13
PublicaciónClinical and translational science
Volumen15
N.º2
DOI
EstadoPublished - feb 2022

ASJC Scopus subject areas

  • General Neuroscience
  • General Biochemistry, Genetics and Molecular Biology
  • General Pharmacology, Toxicology and Pharmaceutics

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