Collaborative AI and Laboratory Medicine integration in precision cardiovascular medicine

被引:21
作者
Gruson, Damien [1 ,2 ,3 ,8 ]
Bernardini, Sergio [4 ,8 ]
Dabla, Pradeep Kumar [5 ,8 ]
Gouget, Bernard [6 ,8 ]
Stankovic, Sanja [7 ,8 ]
机构
[1] Clin Univ St Luc, Dept Clin Biochem, 10 Ave Hippocrate, B-1200 Brussels, Belgium
[2] Catholic Univ Louvain, 10 Ave Hippocrate, B-1200 Brussels, Belgium
[3] Clin Univ St Luc, Pole Rech Endocrinol Diabet & Nutr, Inst Rech Expt & Clin, Brussels, Belgium
[4] Univ Tor Vergata, Dept Expt Med, Rome, Italy
[5] Maulana Azad Med Coll, Dept Biochem, GB Pant Inst Postgrad Med Educ & Res, New Delhi, India
[6] Com Francais Accreditat Cofrac, President Healthcare Div Comm, F-75012 Paris, France
[7] Clin Ctr Serbia, Ctr Med Biochem, Belgrade, Serbia
[8] Int Federat Clin Chem & Lab Med IFCC, Emerging Technol Div MHBLM Comm, Rome, Italy
关键词
Artificial intelligence; Cardiology; Laboratory; Biomarkers; Data; Machine learning; Personalized; EUROPEAN-SOCIETY; MACHINE; PREDICTION; DISEASES;
D O I
10.1016/j.cca.2020.06.001
中图分类号
R446 [实验室诊断]; R-33 [实验医学、医学实验];
学科分类号
1001 ;
摘要
Artificial Intelligence (AI) is a broad term that combines computation with sophisticated mathematical models and in turn allows the development of complex algorithms which are capable to simulate human intelligence such as problem solving and learning. It is devised to promote a significant paradigm shift in the most diverse areas of medical knowledge. On the other hand, Cardiology is a vast field dealing with diseases relating to the heart, the circulatory system, and includes coronary heart disease, cerebrovascular disease, rheumatic heart disease and other conditions. AI has emerged as a promising tool in cardiovascular medicine which is aimed in augmenting the effectiveness of the cardiologist and to extend better quality to patients. It has the ability to support decision-making and improve diagnostic and prognostic performance. Attempt has also been made to explore novel genotypes and phenotypes in existing cardiovascular diseases, improve the quality of patient care, to enable cost-effectiveness with reduce readmission and mortality rates. Our review addresses the integration of AI and laboratory medicine as an accelerator of personalization care associated with the precision and the need of value creation services in cardiovascular medicine.
引用
收藏
页码:67 / 71
页数:5
相关论文
共 36 条
[1]   Cardiovascular Event Prediction by Machine Learning The Multi-Ethnic Study of Atherosclerosis [J].
Ambale-Venkatesh, Bharath ;
Yang, Xiaoying ;
Wu, Colin O. ;
Liu, Kiang ;
Hundley, W. Gregory ;
McClelland, Robyn ;
Gomes, Antoinette S. ;
Folsom, Aaron R. ;
Shea, Steven ;
Guallar, Eliseo ;
Bluemke, David A. ;
Lima, Joao A. C. .
CIRCULATION RESEARCH, 2017, 121 (09) :1092-+
[2]  
[Anonymous], 2019, BMJ OPEN QUAL, DOI DOI 10.3390/PATHOGENS8020060
[3]  
[Anonymous], 2020, EUR HEART J, DOI DOI 10.1093/eurheartj/ehz455
[4]   Diagnosis of Acute Coronary Syndrome with a Support Vector Machine [J].
Berikol, Goksu Bozdereli ;
Yildiz, Oktay ;
Ozcan, I. Turkay .
JOURNAL OF MEDICAL SYSTEMS, 2016, 40 (04) :1-8
[5]  
Brahmbhatt Darshan H, 2019, Card Fail Rev, V5, P86, DOI 10.15420/cfr.2019.5.3
[6]   International Consortium for Health Outcomes Measurement (ICHOM): Standardized Patient-Centered Outcomes Measurement Set for Heart Failure Patients [J].
Burns, Daniel J. P. ;
Arora, Jason ;
Okunade, Oluwakemi ;
Beltrame, John F. ;
Bernardez-Pereira, Sabrina ;
Crespo-Leiro, Marisa G. ;
Filippatos, Gerasimos S. ;
Hardman, Suzanna ;
Hoes, Arno W. ;
Hutchison, Stephen ;
Jessup, Mariell ;
Kinsella, Tina ;
Knapton, Michael ;
Lam, Carolyn S. P. ;
Masoudi, Frederick A. ;
McIntyre, Hugh ;
Mindham, Richard ;
Morgan, Louise ;
Otterspoor, Luuk ;
Parker, Victoria ;
Persson, Hans E. ;
Pinnock, Claude ;
Reid, Christopher M. ;
Riley, Jillian ;
Stevenson, Lynne W. ;
McDonagh, Theresa A. .
JACC-HEART FAILURE, 2020, 8 (03) :212-222
[7]   Data-driven discovery and validation of circulating blood-based biomarkers associated with prevalent atrial fibrillation [J].
Chua, Winnie ;
Purmah, Yanish ;
Cardoso, Victor R. ;
Gkoutos, Georgios, V ;
Tull, Samantha P. ;
Neculau, Georgiana ;
Thomas, Mark R. ;
Kotecha, Dipak ;
Lip, Gregory Y. H. ;
Kirchhof, Paulus ;
Fabritz, Larissa .
EUROPEAN HEART JOURNAL, 2019, 40 (16) :1268-+
[8]   Machine learning-based phenogrouping in heart failure to identify responders to cardiac resynchronization therapy [J].
Cikes, Maja ;
Sanchez-Martinez, Sergio ;
Claggett, Brian ;
Duchateau, Nicolas ;
Piella, Gemma ;
Butakoff, Constantine ;
Pouleur, Anne Catherine ;
Knappe, Dorit ;
Biering-Sorensen, Tor ;
Kutyifa, Valentina ;
Moss, Arthur ;
Stein, Kenneth ;
Solomon, Scott D. ;
Bijnens, Bart .
EUROPEAN JOURNAL OF HEART FAILURE, 2019, 21 (01) :74-85
[9]   Exploring digital technology's potential for cardiology The European Society of Cardiology sponsors the first-ever digital summit [J].
Cowie, Martin R. .
EUROPEAN HEART JOURNAL, 2019, 40 (28) :2283-2284
[10]   e-Health: a position statement of the European Society of Cardiology [J].
Cowie, Martin R. ;
Bax, Jeroen ;
Bruining, Nico ;
Cleland, John G. F. ;
Koehler, Friedrich ;
Malik, Marek ;
Pinto, Fausto ;
van der Velde, Enno ;
Vardas, Panos .
EUROPEAN HEART JOURNAL, 2016, 37 (01) :63-66