Identifying and Predicting Postoperative Infections Based on Readily Available Electronic Health Record Data

被引：2

作者：

van der Meijden, Siri Lise ^{[1
,2
]}

van Boekel, Anna ^{[2
]}

Schinkelshoek, Laurens ^{[1
]}

van Goor, Harry ^{[3
]}

de Boer, Mark ^{[2
]}

Steyerberg, Ewout ^{[2
]}

Geerts, Bart ^{[1
]}

Arbous, Sesmu ^{[2
]}

机构：

[1] Healthplus Ai, Amsterdam, Netherlands

[2] Leiden Univ, Med Ctr, Leiden, Netherlands

[3] Radboud Univ Nijmegen, Med Ctr, Nijmegen, Netherlands

来源：

CARING IS SHARING-EXPLOITING THE VALUE IN DATA FOR HEALTH AND INNOVATION-PROCEEDINGS OF MIE 2023 | 2023年 / 302卷

关键词：

Artificial Intelligence; Prediction; Postoperative infections; Electronic Health Record;

D O I：

10.3233/SHTI230134

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Identification of postoperative infections based on retrospective patient data is currently done using manual chart review. We used a validated, automated labelling method based on registrations and treatments to develop a high-quality prediction model (AUC 0.81) for postoperative infections.

引用

页码：348 / 349

页数：2