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Start of funding 01.07.2023
Personalized Medicine and Prediction Response of Treatments in Rheumatoid Arthritis Using Machine Learning Methods
Prof. Dr. Björn Eskofier
Friedrich-Alexander-University of Erlangen-Nuremberg
Machine Learning and Data Analytics Lab
Prof. Dr. Benjamin Smarr
University of California, San Diego
Smarr Lab, Department of Bioengineering in Medicine
Our study aims to use machine learning approaches to improve treatment response prediction in Rheumatoid Arthritis patients, allowing for tailored care. Our goal is to determine the most effective treatments for individual patients using clinical data analysis and the collaborative efforts of the Machine Learning and Data Analytics Lab at the University of Erlangen-Nuremberg and the Smarr Lab at the University of California, San Diego. The study uses advanced algorithms for machine learning to estimate treatment responses based on data collected, as well as identify important factors related to response outcomes. Finally, this research has the potential to improve Rheumatoid Arthritis therapeutic decision-making, reduce costs, and improve patient outcomes.