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Artificial Intelligence and Postoperative Acute Kidney Injury

Non-cardiac Surgery Clinical Trial

Official title:
Development and Prospective Validation of an Artificial Intelligence Model to Predict Postoperative Acute Kidney Injury

Clinical Trial Summary

The main objective of this study is to develop and validate an artificial intelligence model that predicts postoperative acute kidney injury.

Clinical Trial Description

Postoperative acute kidney injury is known to increase the length of hospital stay and healthcare cost. A lot of risk prediction models have been developed for identifying patients at increased risk of postoperative acute kidney injury. Recent advances in artificial intelligence make it possible to manage and analyze big data. Prediction model using an artificial intelligence and large-scale data can improve the accuracy of prediction performance. Furthermore, the use of an artificial intelligence may be a useful adjuvant tool in making clinical decisions or real-time prediction if it is integrated into the electrical medical record systems. However, before implementing an artificial intelligence model into the clinical setting, prospective evaluation of an artificial intelligence model's real performance is essential. However, to our knowledge, there was no artificial intelligence model for prediction of postoperative acute kidney injury, which was prospectively evaluated. Therefore, we aimed to develop an artificial intelligence model which predicts postoperative acute kidney injury and evaluate the model's performance prospectively. ;

Study Design

Related Conditions & MeSH terms

Clinical Trial Details
NCT number NCT04705064
Study type Observational
Source Seoul National University Hospital
Contact Hyung-Chul Lee, MD.PhD
Phone +821024566336
Email vital@snu.ac.kr
Status Not yet recruiting
Phase
Start date March 1, 2021
Completion date February 1, 2022
View Details
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