1
|
Yasmin F, Shah SMI, Naeem A, Shujauddin SM, Jabeen A, Kazmi S, Siddiqui SA, Kumar P, Salman S, Hassan SA, Dasari C, Choudhry AS, Mustafa A, Chawla S, Lak HM. Artificial intelligence in the diagnosis and detection of heart failure: the past, present, and future. Rev Cardiovasc Med 2021; 22:1095-1113. [PMID: 34957756 DOI: 10.31083/j.rcm2204121] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Revised: 08/16/2021] [Accepted: 08/27/2021] [Indexed: 11/06/2022] Open
Abstract
Artificial Intelligence (AI) performs human intelligence-dependant tasks using tools such as Machine Learning, and its subtype Deep Learning. AI has incorporated itself in the field of cardiovascular medicine, and increasingly employed to revolutionize diagnosis, treatment, risk prediction, clinical care, and drug discovery. Heart failure has a high prevalence, and mortality rate following hospitalization being 10.4% at 30-days, 22% at 1-year, and 42.3% at 5-years. Early detection of heart failure is of vital importance in shaping the medical, and surgical interventions specific to HF patients. This has been accomplished with the advent of Neural Network (NN) model, the accuracy of which has proven to be 85%. AI can be of tremendous help in analyzing raw image data from cardiac imaging techniques (such as echocardiography, computed tomography, cardiac MRI amongst others) and electrocardiogram recordings through incorporation of an algorithm. The use of decision trees by Rough Sets (RS), and logistic regression (LR) methods utilized to construct decision-making model to diagnose congestive heart failure, and role of AI in early detection of future mortality and destabilization episodes has played a vital role in optimizing cardiovascular disease outcomes. The review highlights the major achievements of AI in recent years that has radically changed nearly all areas of HF prevention, diagnosis, and management.
Collapse
Affiliation(s)
- Farah Yasmin
- Department of Internal Medicine, Dow University of Health Sciences, 74200 Karachi, Pakistan
| | | | - Aisha Naeem
- Department of Internal Medicine, Dow University of Health Sciences, 74200 Karachi, Pakistan
| | | | - Adina Jabeen
- Department of Internal Medicine, Dow University of Health Sciences, 74200 Karachi, Pakistan
| | - Sana Kazmi
- Department of Internal Medicine, Dow University of Health Sciences, 74200 Karachi, Pakistan
| | - Sarush Ahmed Siddiqui
- Department of Internal Medicine, Dow University of Health Sciences, 74200 Karachi, Pakistan
| | - Pankaj Kumar
- Department of Internal Medicine, Dow University of Health Sciences, 74200 Karachi, Pakistan
| | - Shiza Salman
- Department of Internal Medicine, Dow Ohja University Hospital, 75330 Karachi, Pakistan
| | - Syed Adeel Hassan
- Department of Cardiovascular Medicine, University of Louisville, Louisville, KY 40292, USA
| | - Chandrashekhar Dasari
- Institute of Molecular Cardiology, School of Medicine, University of Louisville, Louisville, KY 40292, USA
| | - Ali Sanaullah Choudhry
- Department of Internal Medicine, Lahore Medical and Dental College, 53400 Lahore, Pakistan
| | - Ahmad Mustafa
- Department of Internal Medicine, Staten Island University Hospital, Staten Island, NY 10305, USA
| | - Sanchit Chawla
- Department of Internal Medicine, Cleveland Clinic Foundation, Cleveland, OH 44195, USA
| | - Hassan Mehmood Lak
- Department of Internal Medicine, Cleveland Clinic Foundation, Cleveland, OH 44195, USA
| |
Collapse
|