Automatic matching of surgeries to predict surgeons' next actions.

Journal: Artificial intelligence in medicine

PMID: 28343742

Abstract

OBJECTIVE: More than half a million surgeries are performed every day worldwide, which makes surgery one of the most important component of global health care. In this context, the objective of this paper is to introduce a new method for the prediction of the possible next task that a surgeon is going to perform during surgery.

Authors

Germain Forestier
François Petitjean

Faculty of Information Technology, Monash University, Melbourne, Australia. Electronic address: francois.petitjean@monash.edu.
Laurent Riffaud

INSERM MediCIS, Unit U1099 LTSI, University of Rennes 1, Rennes, France; Department of Neurosurgery, Pontchaillou University Hospital, Rennes, France. Electronic address: laurent.riffaud@chu-rennes.fr.
Pierre Jannin

Keywords

Artificial Intelligence Automation Cervical Vertebrae Diskectomy Female Humans Intervertebral Disc Displacement Lumbar Vertebrae Male Middle Aged Motor Activity Motor Skills Operating Room Information Systems Patient Care Team Surgeons Task Performance and Analysis Time Factors

External Resources

View on PubMed Access via DOI PubMed (28343742)

Automatic matching of surgeries to predict surgeons' next actions.

Abstract

Authors

Keywords

External Resources

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