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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| Hauptverfasser: | , , , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
12 September 2017
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| In: |
Nature biomedical engineering
Year: 2017, Jahrgang: 1, Heft: 9, Pages: 691-696 |
| ISSN: | 2157-846X |
| DOI: | 10.1038/s41551-017-0132-7 |
| Online-Zugang: | Verlag, Volltext: http://dx.doi.org/10.1038/s41551-017-0132-7 Verlag, Volltext: https://www.nature.com/articles/s41551-017-0132-7 |
| Verfasserangaben: | Lena Maier-Hein, Swaroop S. Vedula, Stefanie Speidel, Nassir Navab, Ron Kikinis, Adrian Park, Matthias Eisenmann, Hubertus Feussner, Germain Forestier, Stamatia Giannarou, Makoto Hashizume, Darko Katic, Hannes Kenngott, Michael Kranzfelder, Anand Malpani, Keno März, Thomas Neumuth, Nicolas Padoy, Carla Pugh, Nicolai Schoch, Danail Stoyanov, Russell Taylor, Martin Wagner, Gregory D. Hager and Pierre Jannin |
| 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. |
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| Beschreibung: | Gesehen am 20.08.2018 |
| Beschreibung: | Online Resource |
| ISSN: | 2157-846X |
| DOI: | 10.1038/s41551-017-0132-7 |