Establishing a clinical prediction model for diabetic foot ulcers in type 2 diabetic patients with lower extremity arteriosclerotic occlusion using machine learning.

ABSTRACT: The burden of diabetic foot ulcers (DFU) is exacerbated in diabetic patients with concomitant arteriosclerotic occlusion disease (ASO) in the lower extremities, who experience more severe symptoms and poorer prognoses. The study aims to develop a predictive model grounded in machine learning (ML) algorithms, specifically tailored to forecast the occurrence of DFU in diabetic patients with lower extremity ASO. The study involves the data from diabetic patients diagnosed with lower extremity ASO from January 1, 2011 to August 31, 2023. We conducted quality control on the data. Subsequently, the dataset was divided into a training set comprising patients before 2020 and a validation set comprising patients in 2020 and onwards. Patients were stratified into the DFU group or the non-DFU group b

SUBMITTER: Wang Y 

PROVIDER: S-EPMC11972369 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature