Article Synopsis
- Randomized clinical trials are essential for proving the effectiveness and safety of cardiovascular treatments but face challenges like high costs, long durations, and lack of diversity.
- Emerging AI technologies could improve these trials by automating various processes such as patient selection, consent, and outcome analysis.
- However, the use of AI also carries risks, including potential inaccuracies, exacerbation of biases, and privacy concerns, necessitating careful and transparent integration into the trial process.
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Article Abstract
Randomized clinical trials are the gold standard for establishing the efficacy and safety of cardiovascular therapies. However, current pivotal trials are expensive, lengthy, and insufficiently diverse. Emerging artificial intelligence (AI) technologies can potentially automate and streamline clinical trial operations. This review describes opportunities to integrate AI throughout a trial's life cycle, including designing the trial, identifying eligible patients, obtaining informed consent, ascertaining physiological and clinical event outcomes, interpreting imaging, and analyzing or disseminating the results. Nevertheless, AI poses risks, including generating inaccurate results, amplifying biases against underrepresented groups, and violating patient privacy. Medical journals and regulators are developing new frameworks to evaluate AI research tools and the data they generate. Given the high-stakes role of randomized trials in medical decision making, AI must be integrated carefully and transparently to protect the validity of trial results.
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|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12178241 | PMC |
| http://dx.doi.org/10.1016/j.jacc.2024.08.069 | DOI Listing |
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