Dubravka UkalovicSiemens Healthineers
Dubravka Ukalovic
About
4
Publications
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Introduction
Skills and Expertise
Publications
Publications (4)
Objectives
Machine learning models can support an individualized approach in the choice of bDMARDs. We developed prediction models for 5 different bDMARDs using machine learning methods based on patient data derived from the Austrian Biologics Registry (BioReg).
Methods
Data from 1397 patients and 19 variables with at least 100 treat-to-target (t2...
Background
The continuous development of biological disease modifying antirheumatic drugs (bDMARDs) in recent years has significantly improved the treatment options for patients suffering from rheumatoid arthritis. Selecting the most effective biologic remains a challenge, since therapy-response is highly individual depending on the patient history...
Treat-to-target (T2T) is a main therapeutic strategy in rheumatology; however, patients and rheumatologists currently have little support in making the best treatment decision. Clinical decision support systems (CDSSs) could offer this support. The aim of this study was to investigate the accuracy, effectiveness, usability, and acceptance of such a...
BACKGROUND
There have been multiple efforts toward individual prediction of recurrent strokes based on structured clinical and imaging data using machine learning algorithms. Some of these efforts resulted in relatively accurate prediction models. However, acquiring clinical and imaging data is typically possible at provider sites only and is assoc...
