Surgical data science for next-generation interventions.
Lena Maier-Hein,Swaroop Vedula,Stefanie Speidel,Nassir Navab,Nassir Navab,Ron Kikinis,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 M. Pugh,Nicolai Schoch,Danail Stoyanov,Russell H. Taylor,Martin Wagner,Gregory D. Hager,Pierre Jannin,Pierre Jannin +27 more
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TLDR
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.Abstract:
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.read more
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Machine learning for technical skill assessment in surgery: a systematic review
Kyle Lam,Junhong Chen,Zeyu Wang,Fahad Mujtaba Iqbal,Ara Darzi,Benny Lo,Sanjay Purkayastha,James Kinross +7 more
TL;DR: A systematic literature search was performed to identify studies detailing the use of ML for technical skill assessment in surgery as mentioned in this paper , and 66 studies were included, with accuracy rates of over 80% achieved, although tasks and participants varied between studies.
Posted Content
Heidelberg Colorectal Data Set for Surgical Data Science in the Sensor Operating Room
Lena Maier-Hein,Martin Wagner,Tobias Ross,Annika Reinke,Sebastian Bodenstedt,Peter M. Full,Hellena Hempe,Diana Mindroc-Filimon,Patrick Scholz,Thuy Nuong Tran,Pierangela Bruno,Anna Kisilenko,Benjamin Müller,Tornike Davitashvili,Manuela Capek,Minu D. Tizabi,Matthias Eisenmann,Tim Adler,Janek Gröhl,Melanie Schellenberg,Silvia Seidlitz,T. Y. Emmy Lai,Bünyamin Pekdemir,Veith Roethlingshoefer,Fabian Both,Sebastian Bittel,Marc Mengler,Lars Mündermann,Martin Apitz,Annette Kopp-Schneider,Stefanie Speidel,Hannes Kenngott,Beat P. Müller-Stich +32 more
TL;DR: The Heidelberg Colorectal (HeiCo) data set is introduced - the first publicly available data set enabling comprehensive benchmarking of medical instrument detection and segmentation algorithms with a specific emphasis on method robustness and generalization capabilities.
Journal ArticleDOI
Artificial Intelligence for Cataract Detection and Management.
Jocelyn Hui Lin Goh,Zhi Wei Lim,Xiao Ling Fang,Ayesha Anees,Simon Nusinovici,Tyler Hyungtaek Rim,Ching-Yu Cheng,Yih Chung Tham +7 more
TL;DR: This work proposes or derived new AI-based calculation for pre-cataract surgery intraocular lens power, and evaluates deployment angles, feasibility, efficiency, and cost-effectiveness of these new cataract-related AI systems.
Journal ArticleDOI
Impact of data on generalization of AI for surgical intelligence applications
Omri Bar,Daniel Neimark,Maya Zohar,Gregory D. Hager,Ross Girshick,Gerald M. Fried,Tamir Wolf,Dotan Asselmann +7 more
TL;DR: Surgical workflow recognition is assessed and a deep learning system is reported, that not only detects surgical phases, but does so with high accuracy and is able to generalize to new settings and unseen medical centers.
Journal ArticleDOI
Multi-task temporal convolutional networks for joint recognition of surgical phases and steps in gastric bypass procedures.
Sanat Ramesh,Sanat Ramesh,Diego Dall'Alba,Cristians Gonzalez,Tong Yu,Pietro Mascagni,Pietro Mascagni,Didier Mutter,Jacques Marescaux,Paolo Fiorini,Nicolas Padoy +10 more
TL;DR: In this paper, a multi-task multi-stage temporal convolutional network (MTMS-TCN) was proposed to jointly predict the phases and steps and benefit from their complementarity to better evaluate the execution of the procedure.
References
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An estimation of the global volume of surgery: a modelling strategy based on available data
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