Article

Two-Stage Machine Learning Based Prediction of Thrombophilia Management

2025-10-23

Abstract excerpt

Thrombophilia diagnosis and management rely on the nuanced interpretation of clinical history, risk factors, and laboratory data, yet significant variability exists in clinical practice due to subjective assessment, institutional differences, and limited consensus guidelines. In this retrospective study, we evaluated the use of a two-stage machine learning (ML) approach to predict thrombophilia diagnosis and subse...

Topics

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

Identifiers and source

Literature Corpus work: 1dde9651-5400-5e26-a9cd-6c4a48ffb55f
DOI: 10.1101/2025.10.22.25338547

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Two-Stage Machine Learning Based Prediction of Thrombophilia ManagementDOI 10.1101/2025.10.22.25338547Read

Facilitating clinical trials in Polycythemia vera (PV) by identifying patient cohorts at high near-term risk of thrombosis using rich data and machine learningSemantic proximity Read

Analysis of clinical factors in first diagnosis of immune thrombotic thrombocytopenic purpura with report of 6 casesSemantic proximity Read

Development and validation of a multiple factor-based prognostic score system of thrombosis in polycythemia vera (MFPS-PV)Semantic proximity Read

Prediction of inhibitors in hemophilia.Semantic proximity Read

Application of machine learning approaches for predicting hemophilia A severity.Semantic proximity Read

Ability of Caprini and Padua Risk-Assessment Models to Predict Venous Thromboembolism in a Nationwide StudySemantic proximity Read

An open-source, configurable machine learning pipeline for predicting blood culture outcomes from routine haematology parametersSemantic proximity Read

An open-source, configurable machine learning pipeline for predicting blood culture outcomes from routine haematology parametersSemantic proximity Read

[Analysis of risk factors for venous thromboembolism in patients with polycythemia vera and establishment of a prediction model].Semantic proximity Read

RhDnostics: A Machine Learning-Based Predictive Algorithm Model for RhD-Negative and DEL Blood Group Screening.Semantic proximity Read

Validation of the revised International Prognostic Score of Thrombosis for Essential Thrombocythemia (IPSET-thrombosis) in 585 Mayo Clinic patients.Semantic proximity Read

A machine learning model for the prediction of peripherally inserted central catheter-related venous thrombosis among high-risk adult patientsSemantic proximity Read