Artificial intelligence (AI) has generated significant expectation in the healthcare industry, particularly as a transformative factor in diagnosis, treatment, and patient care. Although its implementation continues to evolve, the majority of current AI applications remain limited to administrative and non-clinical functions, such as chatbots, computerized scheduling, and electronic triage systems. For AI to have a transformative impact on clinical practice, clinicians with first-hand knowledge of patient care dynamics and healthcare systems' real-world demands must lead the deployment of AI. In cardiovascular medicine, AI can make a considerable impact by integrating data from diverse sources—like wearable sensors, laboratory tests, and patient-reported outcomes—to detect early clinical changes and enable personalized follow-up. General public use of wearable devices provides an opportunity for continuous monitoring of patients, if the data thus created is filtered and interpreted through a clinically sound framework. Such a transformation helps develop adaptive and efficient models of follow-up that not only optimize resource use but also improve quality of care. The active engagement of doctors as designers of medical technology is imperative to make sure that digitalization is kept patient-centric and not focused on system efficiency only. If well integrated, AI has the potential to augment clinical responsiveness, enhance the doctor–patient relationship, and help create a more efficient, sustainable, and human-oriented healthcare system.
Felipe et al. (Wed,) studied this question.
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