Identifying the Risk of Sepsis in Patients With Cancer Using Digital Health Care Records: Machine Learning-Based Approach.

Dong-Hun Yang Jimin Kim Junsang Yoo Won Chul Cha Hyojung Paik

Published in: JMIR medical informatics (2022)

We showed that lab tests and medication relationships can be used as efficient features for predicting sepsis in patients with cancer. Consequently, identifying the risk of sepsis in patients with cancer using EHRs and machine learning is feasible.

Keyphrases

machine learning
septic shock
acute kidney injury
healthcare
intensive care unit
artificial intelligence
big data
deep learning
affordable care act
electronic health record