Surgical Planning Laboratory - Brigham & Women's Hospital - Boston, Massachusetts USA - a teaching affiliate of Harvard Medical School

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Surgical Data Science for Next-generation Interventions

Institution:
Division Computer Assisted Medical Interventions (CAMI), German Cancer Research Center (DKFZ), Heidelberg, Germany
Publication Date:
Sep-2017
Journal:
Nature Biomedical Engineering.
Volume Number:
1
Pages:
691–6
Citation:
Nature Biomedical Engineering. 2017 Sep; 1:691–6.
Links:
https://www.nature.com/articles/s41551-017-0132-7
Appears in Collections:
NAC, NCIGT, SPL
Sponsors:
R01 EB01152407S1/EB/NIBIB NIH HHS/United States
P41 EB015902/EB/NIBIB NIH HHS/United States
U24 CA180918/CA/NCI NIH HHS/United States
P41 EB015898/EB/NIBIB NIH HHS/United States
R01 EB014955/EB/NIBIB NIH HHS/United States
DOD-W81XWH-13-1-0080
Generated Citation:
Maier-Hein L., Vedula S.S., Speidel S., Navab N., Kikinis R., Park A., Eisenmann M., Feussner H., Forestier G., Giannarou S., Hashizume M., Katic D., Kenngott H., Kranzfelder M., Malpani A., März K., Neumuth T., Padoy N., Pugh C., Schoch N., Stoyanov D., Taylor R., Wagner M., Hager G.D., Jannin P. Surgical Data Science for Next-generation Interventions. Nature Biomedical Engineering. 2017 Sep; 1:691–6.
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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.