#1
Bedside Computer Vision — Moving Artificial Intelligence from Driver Assistance to Patient Safety
Serena Yeung, M.S., N. Lance Downing, M.D., Li Fei‑Fei, Ph.D., and Arnold Milstein, M.D., M.P.H.
NEJM 378;14 April 5, 2018
DOI: 10.1056/NEJMp1716891
#2
Learning to Learn
Chelsea Finn Jul 18, 2017
https://bair.berkeley.edu/blog/2017/07/18/learning-to-learn/
#3
Machine Learning and Prediction in Medicine — Beyond the Peak of Inflated Expectations
Jonathan H. Chen, M.D., Ph.D., and Steven M. Asch, M.D., M.P.H.
NEJM 376;26 June 29, 2017
DOI: 10.1056/NEJMp1702071
#4
Deaths by horsekick in the Prussian army – and other ‘Never Events’ in large organisations
J. J. Pandit
Anaesthesia 2016, 71, 3–16
DOI:10.1111/anae.13261
#5
2017 ESC/EACTS Guidelines for the management of valvular heart disease
The Task Force for the Management of Valvular Heart Disease of the European Society of Cardiology
(ESC) and the European Association for Cardio-Thoracic Surgery (EACTS)
European Journal of Cardio-Thoracic Surgery 52 (2017) 616–664
doi:10.1093/ejcts/ezx324
#6
2018 ESC/EACTS Guidelines on myocardial revascularization
The Task Force on myocardial revascularization of the European Society of Cardiology (ESC)
and European Association for Cardio-Thoracic Surgery (EACTS)
European Heart Journal (2019) 40, 87–165
doi:10.1093/eurheartj/ehy394
#7
Artificial intelligence-assisted care in medicine: a revolution or yet another blunt weapon?
Potentials, challenges, and the future of implementing artificial intelligence (AI) for clinical care
Alexander Meyer
European Heart Journal
doi:10.1093/eurheartj/ehz701
#8
Predictive Utility of a Machine Learning Algorithm in Estimating Mortality Risk in Cardiac Surgery
Arman Kilic
The Annals of Thoracic Surgery
https://doi.org/10.1016/j.athoracsur.2019.09.049
#9
Moving beyond regression techniques in cardiovascular risk prediction: applying machine learning to address analytic challenges
Benjamin A. Goldstein, Ann Marie Navar, and Rickey E. Carter
European Heart Journal
doi:10.1093/eurheartj/ehw302