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1
'Fit-for-purpose?' - challenges and opportunities for applications of blockchain technology in the future of healthcare
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Artigo
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'Fit-for-purpose?' - challenges and opportunities for applications of blockchain technology in the future of healthcare

Mackey, Tim K ; Kuo, Tsung-Ting ; Gummadi, Basker ; Clauson, Kevin A ; Church, George ; Grishin, Dennis ; Obbad, Kamal ; Barkovich, Robert ; Palombini, Maria

BMC medicine, 2019-03, Vol.17 (1), p.68-68, Article 68 [Periódico revisado por pares]

England: BioMed Central Ltd

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2
Unintended Consequences of Machine Learning in Medicine
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Unintended Consequences of Machine Learning in Medicine

Cabitza, Federico ; Rasoini, Raffaele ; Gensini, Gian Franco

JAMA : the journal of the American Medical Association, 2017-08, Vol.318 (6), p.517-518 [Periódico revisado por pares]

United States: American Medical Association

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3
Artificial Intelligence and Machine Learning in Clinical Medicine, 2023
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Artigo
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Artificial Intelligence and Machine Learning in Clinical Medicine, 2023

Haug, Charlotte J. ; Drazen, Jeffrey M. Drazen, Jeffrey M. ; Leong, Tze-Yun ; Kohane, Isaac S.

The New England journal of medicine, 2023-03, Vol.388 (13), p.1201-1208 [Periódico revisado por pares]

United States: Massachusetts Medical Society

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4
The NASSS framework for ex post theorisation of technology-supported change in healthcare: worked example of the TORPEDO programme
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Artigo
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The NASSS framework for ex post theorisation of technology-supported change in healthcare: worked example of the TORPEDO programme

Abimbola, Seye ; Patel, Bindu ; Peiris, David ; Patel, Anushka ; Harris, Mark ; Usherwood, Tim ; Greenhalgh, Trisha

BMC medicine, 2019-12, Vol.17 (1), p.233-233, Article 233 [Periódico revisado por pares]

England: BioMed Central Ltd

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5
The WHO 2016 verbal autopsy instrument: An international standard suitable for automated analysis by InterVA, InSilicoVA, and Tariff 2.0
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Artigo
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The WHO 2016 verbal autopsy instrument: An international standard suitable for automated analysis by InterVA, InSilicoVA, and Tariff 2.0

Nichols, Erin K ; Byass, Peter ; Chandramohan, Daniel ; Clark, Samuel J ; Flaxman, Abraham D ; Jakob, Robert ; Leitao, Jordana ; Maire, Nicolas ; Rao, Chalapati ; Riley, Ian ; Setel, Philip W

PLoS medicine, 2018-01, Vol.15 (1), p.e1002486-e1002486 [Periódico revisado por pares]

United States: Public Library of Science

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6
Response to COVID-19 in Taiwan: Big Data Analytics, New Technology, and Proactive Testing
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Artigo
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Response to COVID-19 in Taiwan: Big Data Analytics, New Technology, and Proactive Testing

Wang, C. Jason ; Ng, Chun Y ; Brook, Robert H

JAMA : the journal of the American Medical Association, 2020-04, Vol.323 (14), p.1341-1342 [Periódico revisado por pares]

United States: American Medical Association

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7
Deep Learning—A Technology With the Potential to Transform Health Care
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Artigo
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Deep Learning—A Technology With the Potential to Transform Health Care

Hinton, Geoffrey

JAMA : the journal of the American Medical Association, 2018-09, Vol.320 (11), p.1101-1102 [Periódico revisado por pares]

United States: American Medical Association

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8
Convergence of Implementation Science, Precision Medicine, and the Learning Health Care System: A New Model for Biomedical Research
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Convergence of Implementation Science, Precision Medicine, and the Learning Health Care System: A New Model for Biomedical Research

Chambers, David A ; Feero, W. Gregory ; Khoury, Muin J

JAMA : the journal of the American Medical Association, 2016-05, Vol.315 (18), p.1941-1942 [Periódico revisado por pares]

United States: American Medical Association

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9
A Decade of Health Information Technology Usability Challenges and the Path Forward
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A Decade of Health Information Technology Usability Challenges and the Path Forward

Ratwani, Raj M ; Reider, Jacob ; Singh, Hardeep

JAMA : the journal of the American Medical Association, 2019-02, Vol.321 (8), p.743-744 [Periódico revisado por pares]

United States: American Medical Association

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10
Perceptions of medical students towards online teaching during the COVID-19 pandemic: a national cross-sectional survey of 2721 UK medical students
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Artigo
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Perceptions of medical students towards online teaching during the COVID-19 pandemic: a national cross-sectional survey of 2721 UK medical students

Dost, Samiullah ; Hossain, Aleena ; Shehab, Mai ; Abdelwahed, Aida ; Al-Nusair, Lana

BMJ open, 2020-11, Vol.10 (11), p.e042378-e042378 [Periódico revisado por pares]

England: BMJ Publishing Group LTD

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