Digital Twin of Rheuma
Project leader: Björn Eskofier
Project members: Fatemeh Salehihafshejani
Start date: 1. September 2021
End date: 30. August 2024
Funding source: d.hip
There is a wide range of medications for RA patients, Clinical trials and real-time experience demonstrate that sometimes these treatments have adverse effects, for better benefits and later minimizing the damage, we should predict the response for each person.
This project aims to collect medical data on rheumatology arthritis, select the best factors and identify important clinical features associated with remission and then create a model to predict remissions in patients and prediction of treatment response and course of activity for each patient using machine learning methods. This project could help in preventing wrong prescriptions and time-wasting before disease progression.
We want to reach the aim by using medical data collected and recorded by rheumatologists from patient characteristics, disease courses, laboratory data, and medication data. Our partners from the medicine side are helping to collect and access existing data. The partners in MaD-Lab carry out Machine learning and data analytics approaches on them to find a remission or development of the prognostic model.