Development and validation of deep vein thrombosis diagnostic model based on machine learning methods.

ABSTRACT: The D-Dimer testing has limited diagnostic value for patients with a deep venous thrombosis (DVT) probability based on clinical prediction rules. There are still patients with normal D-Dimer levels (< 500 ng/mL) diagnosed with DVT. Some new predictive marker may improve the predictive power of D-Dimer, especially in DVT patients with normal levels of D-Dimer. All subjects were from Nanyang Central Hospital. The demographic data and laboratory test data were collected. Multiple models were used to evaluate and calculate the importance rank. Multivariate logistics was used to establish a DVT diagnostic model. Compared to D-Dimer and other markers, this combined model has better performance. The von Willebrand factor Gain-of-function mutant GPIb binding assays (VWF: GPIbM) can improve the dia

SUBMITTER: Yan B 

PROVIDER: S-EPMC12619743 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature