The Role of Artificial Intelligence in Improving Patient Outcomes and Future of Healthcare Delivery in Cardiology: A Narrative Review of the Literature.
Dhir Niren GalaHaditya BehlMili ShahAmgad N MakaryusPublished in: Healthcare (Basel, Switzerland) (2024)
Cardiovascular diseases exert a significant burden on the healthcare system worldwide. This narrative literature review discusses the role of artificial intelligence (AI) in the field of cardiology. AI has the potential to assist healthcare professionals in several ways, such as diagnosing pathologies, guiding treatments, and monitoring patients, which can lead to improved patient outcomes and a more efficient healthcare system. Moreover, clinical decision support systems in cardiology have improved significantly over the past decade. The addition of AI to these clinical decision support systems can improve patient outcomes by processing large amounts of data, identifying subtle associations, and providing a timely, evidence-based recommendation to healthcare professionals. Lastly, the application of AI allows for personalized care by utilizing predictive models and generating patient-specific treatment plans. However, there are several challenges associated with the use of AI in healthcare. The application of AI in healthcare comes with significant cost and ethical considerations. Despite these challenges, AI will be an integral part of healthcare delivery in the near future, leading to personalized patient care, improved physician efficiency, and anticipated better outcomes.
Keyphrases
- artificial intelligence
- healthcare
- clinical decision support
- big data
- machine learning
- deep learning
- electronic health record
- end stage renal disease
- cardiovascular disease
- ejection fraction
- newly diagnosed
- primary care
- current status
- case report
- chronic kidney disease
- climate change
- health information
- risk assessment
- decision making
- adipose tissue
- health insurance
- metabolic syndrome
- affordable care act
- peritoneal dialysis
- quality improvement
- acute kidney injury
- weight loss
- data analysis