Utilizing Machine Learning and Automated Performance Metrics to Evaluate Robot-Assisted Radical Prostatectomy Performance and Predict Outcomes

Journal of Endourology

Volumn 32, Issue 5, 2018, Pages 438-444

  Hung, Andrew J ^a   Chen, Jian ^a   Che, Zhengping ^b   Nilanon, Tanachat ^b   Jarc, Anthony ^c   Titus, Micha ^a   Oh, Paul J ^a   Gill, Inderbir S ^a   Liu, Yan ^b  

^a UNIVERSITY OF SOUTHERN CALIFORNIA   (United States)

^b University of Southern California   (United States)

^c INTUITIVE SURGICAL INC   (United States)

Author keywords

artificial intelligence; education; prostate neoplasms; robotic surgical procedures

Indexed keywords

ADULT; AGED; ARTICLE; CANCER PROGNOSIS; COMPUTER PREDICTION; CONTROLLED STUDY; HUMAN; LENGTH OF STAY; MACHINE LEARNING; MAJOR CLINICAL STUDY; MALE; MEASUREMENT ACCURACY; OPERATION DURATION; PRIORITY JOURNAL; PROSTATE ADENOCARCINOMA; RANDOM FOREST; ROBOT-ASSISTED PROSTATECTOMY; ALGORITHM; FACTUAL DATABASE; MIDDLE AGED; PROCEDURES; PROSTATE TUMOR; PROSTATECTOMY; ROBOTIC SURGICAL PROCEDURE;

AGED; ALGORITHMS; DATABASES, FACTUAL; HUMANS; MACHINE LEARNING; MALE; MIDDLE AGED; OPERATIVE TIME; PROSTATECTOMY; PROSTATIC NEOPLASMS; ROBOTIC SURGICAL PROCEDURES;

EID: 85046895631     PISSN: 08927790     EISSN: 1557900X     Source Type: Journal    
DOI: 10.1089/end.2018.0035     Document Type: Article

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