Can a deep learning model based on intraoperative time-series monitoring data predict post-hysterectomy quality of recovery?

Autor:	Xu Zhao, Ke Liao, Wei Wang, Junmei Xu, Lingzhong Meng
Jazyk:	angličtina
Rok vydání:	2021
Předmět:	Deep learning Machine learning Time-series monitoring data Hysterectomy Quality of recovery Prediction Surgery RD1-811
Zdroj:	Perioperative Medicine, Vol 10, Iss 1, Pp 1-12 (2021)
Druh dokumentu:	article
ISSN:	2047-0525
DOI:	10.1186/s13741-021-00178-4
Popis:	Abstract Background Intraoperative physiological monitoring generates a large quantity of time-series data that might be associated with postoperative outcomes. Using a deep learning model based on intraoperative time-series monitoring data to predict postoperative quality of recovery has not been previously reported. Methods Perioperative data from female patients having laparoscopic hysterectomy were prospectively collected. Deep learning, logistic regression, support vector machine, and random forest models were trained using different datasets and evaluated by 5-fold cross-validation. The quality of recovery on postoperative day 1 was assessed using the Quality of Recovery-15 scale. The quality of recovery was dichotomized into satisfactory if the score ≥122 and unsatisfactory if
Databáze:	Directory of Open Access Journals
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