Back to search

Article

Explainable predictions of a machine learning model to forecast the postoperative length of stay for severe patients

2022-11-29

Abstract excerpt

Understanding the length of stay of severe patients who require general anesthesia is key to enhancing health outcomes. Here, we aim to discover how machine learning can support resource allocation management and decision-making resulting from the length of stay prediction. A retrospective cohort study was conducted from January 2018 to October 2020. A total cohort of 240,000 patients’ medical records was collecte...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
c3314a1e-f3ca-5a4b-9f36-cdafca167f59
DOI
10.21203/rs.3.rs-2298843/v1
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
Explainable predictions of a machine learning model to forecast the postoperative length of stay for severe patientsDOI 10.21203/rs.3.rs-2298843/v1
Select a neighboring publication to make it the new centre.