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How to Read Articles That Use Machine Learning: Users’ Guides to the Medical Literature
How to Read Articles That Use Machine Learning: Users’ Guides to the Medical Literature
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How to Read Articles That Use Machine Learning: Users’ Guides to the Medical Literature

Liu, Yun ; Chen, Po-Hsuan Cameron ; Krause, Jonathan ; Peng, Lily

JAMA : the journal of the American Medical Association, 2019-11, Vol.322 (18), p.1806-1816 [Periódico revisado por pares]

United States: American Medical Association

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2
Implementing Machine Learning in Health Care — Addressing Ethical Challenges
Implementing Machine Learning in Health Care — Addressing Ethical Challenges
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Implementing Machine Learning in Health Care — Addressing Ethical Challenges

Char, Danton S ; Shah, Nigam H ; Magnus, David

The New England journal of medicine, 2018-03, Vol.378 (11), p.981-983 [Periódico revisado por pares]

United States: Massachusetts Medical Society

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3
From machine learning to machine reasoning: An essay
From machine learning to machine reasoning: An essay
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From machine learning to machine reasoning: An essay

Bottou, Léon

Machine learning, 2014-02, Vol.94 (2), p.133-149 [Periódico revisado por pares]

New York: Springer US

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4
Machine Learning for Surgical Phase Recognition: A Systematic Review
Machine Learning for Surgical Phase Recognition: A Systematic Review
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Machine Learning for Surgical Phase Recognition: A Systematic Review

Garrow, Carly R ; Kowalewski, Karl-Friedrich ; Li, Linhong ; Wagner, Martin ; Schmidt, Mona W ; Engelhardt, Sandy ; Hashimoto, Daniel A ; Kenngott, Hannes G ; Bodenstedt, Sebastian ; Speidel, Stefanie ; Müller-Stich, Beat P ; Nickel, Felix

Annals of surgery, 2021-04, Vol.273 (4), p.684-693 [Periódico revisado por pares]

United States: Copyright Wolters Kluwer Health, Inc. All rights reserved

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5
Machine learning–enabled high-entropy alloy discovery
Machine learning–enabled high-entropy alloy discovery
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Machine learning–enabled high-entropy alloy discovery

Rao, Ziyuan ; Tung, Po-Yen ; Xie, Ruiwen ; Wei, Ye ; Zhang, Hongbin ; Ferrari, Alberto ; Klaver, T.P.C. ; Körmann, Fritz ; Sukumar, Prithiv Thoudden ; Kwiatkowski da Silva, Alisson ; Chen, Yao ; Li, Zhiming ; Ponge, Dirk ; Neugebauer, Jörg ; Gutfleisch, Oliver ; Bauer, Stefan ; Raabe, Dierk

Science (American Association for the Advancement of Science), 2022-10, Vol.378 (6615), p.78-85 [Periódico revisado por pares]

Washington: The American Association for the Advancement of Science

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6
Predicting the Future — Big Data, Machine Learning, and Clinical Medicine
Predicting the Future — Big Data, Machine Learning, and Clinical Medicine
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Predicting the Future — Big Data, Machine Learning, and Clinical Medicine

Obermeyer, Ziad ; Emanuel, Ezekiel J

The New England journal of medicine, 2016-09, Vol.375 (13), p.1216-1219 [Periódico revisado por pares]

United States: Massachusetts Medical Society

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7
Cardiovascular Event Prediction by Machine Learning: The Multi-Ethnic Study of Atherosclerosis
Cardiovascular Event Prediction by Machine Learning: The Multi-Ethnic Study of Atherosclerosis
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Cardiovascular Event Prediction by Machine Learning: The Multi-Ethnic Study of Atherosclerosis

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, João A.C

Circulation research, 2017-10, Vol.121 (9), p.1092-1101 [Periódico revisado por pares]

United States: American Heart Association, Inc

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8
Machine Learning to Classify Intracardiac Electrical Patterns During Atrial Fibrillation: Machine Learning of Atrial Fibrillation
Machine Learning to Classify Intracardiac Electrical Patterns During Atrial Fibrillation: Machine Learning of Atrial Fibrillation
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Machine Learning to Classify Intracardiac Electrical Patterns During Atrial Fibrillation: Machine Learning of Atrial Fibrillation

Alhusseini, Mahmood I ; Abuzaid, Firas ; Rogers, Albert J ; Zaman, Junaid A.B ; Baykaner, Tina ; Clopton, Paul ; Bailis, Peter ; Zaharia, Matei ; Wang, Paul J ; Rappel, Wouter-Jan ; Narayan, Sanjiv M

Circulation. Arrhythmia and electrophysiology, 2020-08, Vol.13 (8), p.e008160-e008160 [Periódico revisado por pares]

United States: American Heart Association, Inc

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9
Diagnostic Accuracy of a Machine-Learning Approach to Coronary Computed Tomographic Angiography-Based Fractional Flow Reserve: Result From the MACHINE Consortium
Diagnostic Accuracy of a Machine-Learning Approach to Coronary Computed Tomographic Angiography-Based Fractional Flow Reserve: Result From the MACHINE Consortium
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Diagnostic Accuracy of a Machine-Learning Approach to Coronary Computed Tomographic Angiography-Based Fractional Flow Reserve: Result From the MACHINE Consortium

Coenen, Adriaan ; Kim, Young-Hak ; Kruk, Mariusz ; Tesche, Christian ; De Geer, Jakob ; Kurata, Akira ; Lubbers, Marisa L ; Daemen, Joost ; Itu, Lucian ; Rapaka, Saikiran ; Sharma, Puneet ; Schwemmer, Chris ; Persson, Anders ; Schoepf, U Joseph ; Kepka, Cezary ; Hyun Yang, Dong ; Nieman, Koen

Circulation. Cardiovascular imaging, 2018-06, Vol.11 (6), p.e007217-e007217 [Periódico revisado por pares]

United States

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10
Machine Learning and Prediction in Medicine — Beyond the Peak of Inflated Expectations
Machine Learning and Prediction in Medicine — Beyond the Peak of Inflated Expectations
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Machine Learning and Prediction in Medicine — Beyond the Peak of Inflated Expectations

Chen, Jonathan H ; Asch, Steven M

The New England journal of medicine, 2017-06, Vol.376 (26), p.2507-2509 [Periódico revisado por pares]

United States: Massachusetts Medical Society

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