Rishith Mishra, Hersh Patel, Aleena Jamal, Som Singh
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Potential role of large language models and personalized medicine to innovate cardiac rehabilitation.
Cardiac rehabilitation is a crucial multidisciplinary approach to improve patient outcomes. There is a growing body of evidence that suggests that these programs contribute towards reducing cardiovascular mortality and recurrence. Despite this, cardiac rehabilitation is underutilized and adherence to these programs has been a demonstrated barrier in achieving these outcomes. As a result, there is a growing focus on innovating these programs, especially from the standpoint of digital health and personalized medicine. This editorial discusses the possible roles of large language models, such as their role in ChatGPT, in further personalizing cardiac rehabilitation programs through simplifying medical jargon and employing motivational interviewing techniques, thus boosting patient engagement and adherence. However, these possibilities must be further investigated in the clinical literature. Likewise, the integration of large language models in cardiac rehabilitation will be challenging in its nascent stages to ensure accurate and ethical information delivery.
期刊介绍:
The World Journal of Clinical Cases (WJCC) is a high-quality, peer reviewed, open-access journal. The primary task of WJCC is to rapidly publish high-quality original articles, reviews, editorials, and case reports in the field of clinical cases. In order to promote productive academic communication, the peer review process for the WJCC is transparent; to this end, all published manuscripts are accompanied by the anonymized reviewers’ comments as well as the authors’ responses. The primary aims of the WJCC are to improve diagnostic, therapeutic and preventive modalities and the skills of clinicians and to guide clinical practice in clinical cases.