Utilizing machine learning and automated performance metrics to evaluate robot-assisted radical prostatectomy performance and predict outcomes

Jian Chen
Jian Chen
Tanachat Nilanon
Tanachat Nilanon
Micha Titus
Micha Titus

JOURNAL OF ENDOUROLOGY, pp. 438-444, 2018.

Cited by: 26|Views18
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Abstract:

Purpose: Surgical performance is critical for clinical outcomes. We present a novel machine learning (ML) method of processing automated performance metrics (APMs) to evaluate surgical performance and predict clinical outcomes after robot-assisted radical prostatectomy (RARP). Materials and Methods: We trained three ML algorithms utilizin...More

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