Surgical data science for next-generation interventions

Interventional healthcare will evolve from an artisanal craft based on the individual experiences, preferences and traditions of physicians into a discipline that relies on objective decision-making on the basis of large-scale data from heterogeneous sources.

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Bibliographische Detailangaben
Veröffentlicht in:	Nature biomedical engineering 2017-09, Vol.1 (9), p.691-696
Hauptverfasser:	Maier-Hein, Lena, Vedula, Swaroop S., Speidel, Stefanie, Navab, Nassir, Kikinis, Ron, Park, Adrian, Eisenmann, Matthias, Feussner, Hubertus, Forestier, Germain, Giannarou, Stamatia, Hashizume, Makoto, Katic, Darko, Kenngott, Hannes, Kranzfelder, Michael, Malpani, Anand, März, Keno, Neumuth, Thomas, Padoy, Nicolas, Pugh, Carla, Schoch, Nicolai, Stoyanov, Danail, Taylor, Russell, Wagner, Martin, Hager, Gregory D., Jannin, Pierre
Format:	Artikel
Sprache:	eng
Schlagworte:	692/700 692/700/565/545 Biomedical Engineering/Biotechnology Biomedicine Caregivers Comment Computer Science Data science Decision making Gastroenterology Knowledge Medical equipment Other Patients Physicians Radiation therapy Surgery
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Beschreibung
Zusammenfassung:	Interventional healthcare will evolve from an artisanal craft based on the individual experiences, preferences and traditions of physicians into a discipline that relies on objective decision-making on the basis of large-scale data from heterogeneous sources.
ISSN:	2157-846X 2157-846X
DOI:	10.1038/s41551-017-0132-7