Federated Artificial Intelligence Framework for Optimizing Pancreatic Cancer Treatment

The “FAIrPaCT” research network, funded by the BMBF under the National Decade Against Cancer initiative, aims to develop a federated AI software system to predict the success of individual pancreatic cancer treatments and identify factors that improve therapy effectiveness. With insights gained from analyzing molecular mechanisms, the project strives for advanced, personalized medications and treatment strategies. Utilizing federated learning, FAIrPaCT leverages diverse data sets, including clinical and molecular data from Germany’s largest patient cohorts, while ensuring high data protection standards by analyzing data across devices without central storage. The network collaborates with major German medical centers, including the University Medical Center Göttingen and the University Hospital of Gießen and Marburg, to harness unique and extensive data for their groundbreaking work.

Successful Workshop on Federated Ensemble Learning at ISMB 2024

Successful Workshop on Federated Ensemble Learning at ISMB 2024 We are pleased to announce the successful completion of the workshop titled ‘Federated Ensemble Learning for Biomedical Data’, held during the prestigious ISMB 2024 conference in Montreal on July 12th. The workshop was organized by Anne-Christin Hauschild, Youngjun Park, Hryhorii Chereda, and Maryam Moradpour as part […]
Poster : Federated Artificial Intelligence fRamework for PAncreatic Cancer Treatment

Location University of Göttingen/ University Medical Center Göttingen Department of Medicals Informatics (UMG) Prof. Dr. Anne-Christin Hausschild (Coordinator, PI WP1, WP2) Prof. Dr. Uli Sax (PI WP3, WP7) Department of Medical Bioinformatics (UMG) Prof. Tim Beißbarth (PI, WP6) Dr. Gregory Chereda Clinic for General, Visceral and Paediatric Surgery Clinic for Gastroenterology, Gastrointestinal Oncology and Endocrinology Prof. Dr. Elisabeth Hessmann (PI, WP3) Prof.…
About the Project

The “FAIrPaCT” research network is funded by the BMBF as part of the National Decade Against Cancer and aims to develop a software system that can individually predict the probability of success of pancreatic cancer therapies. This should increase the chances of effective treatment. In addition, factors could be identified that positively influence the effectiveness […]
Project goals

Artificial intelligence for better therapies. The research team now wants to analyze this data together. The software system that medical IT specialists develop on this basis should be able to estimate the probability of success for specific treatment approaches. Since the data comes from three different locations, the calculations go beyond the boundaries of one location. In the future, the system will be usable regardless of…