Harnessing artificial intelligence in cardiac rehabilitation, a systematic review.
Sara SotirakosBasem FoudaNoor Adeebah Mohamed RazifNiall CribbenCormac MulhallAisling O'ByrneBridget MoranRuairi ConnollyPublished in: Future cardiology (2021)
Aim: This systematic review aims to evaluate the current body of research surrounding the efficacy of artificial intelligence (AI) in cardiac rehabilitation. Presently, AI can be incorporated into personal devices such as smart watches and smartphones, in diagnostic and home monitoring devices, as well as in certain inpatient care settings. Materials & methods: The PRISMA guidelines were followed in this review. Inclusion and exclusion criteria were set using the Population, Intervention, Comparison and Outcomes (PICO) tool. Results: Eight studies meeting the inclusion criteria were found. Conclusion: Incorporation of AI into healthcare, cardiac rehabilitation delivery, and monitoring holds great potential for early detection of cardiac events, allowing for home-based monitoring, and improved clinician decision making.
Keyphrases
- artificial intelligence
- big data
- healthcare
- machine learning
- systematic review
- deep learning
- decision making
- meta analyses
- palliative care
- randomized controlled trial
- left ventricular
- mental health
- heart failure
- clinical practice
- risk assessment
- affordable care act
- chronic pain
- climate change
- atrial fibrillation
- clinical evaluation