Risk Prediction of Diabetic Foot Amputation Using Machine Learning and Explainable Artificial Intelligence.

ABSTRACT:

Background

Diabetic foot ulcers (DFUs) are serious complications of diabetes which can lead to lower extremity amputations (LEAs). Risk prediction models can identify high-risk patients who can benefit from early intervention. Machine learning (ML) methods have shown promising utility in medical applications. Explainable modeling can help its integration and acceptance. This study aims to develop a risk prediction model using ML algorithms with explainability for LEA in DFU patients.

Methods

This study is a retrospective review of 2559 inpatient DFU episodes in a tertiary institution from 2012 to 2017. Fifty-one features including patient demographics, comorbidities, medication, wound characteristics, and laboratory results were reviewed. Outcome measures were the risk of ma

SUBMITTER: Oei CW 

PROVIDER: S-EPMC11571574 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature