ATLAS

Liver cancer is the second leading cause of cancer-related death. Its diagnosis and treatment demand timely, patient-specific pathways. Medical decisions involve interdependent factors from diverse disciplines, past experiences, and guidelines. Combining these factors with therapy options poses a major challenge for physicians.

In this project, we develop ATLAS, an AI-powered decision support tool, to aid clinicians for liver cancer diagnosis and treatment. Experts in surgical oncology, mathematical modeling, and machine learning are collaboratively developing this tool. In particular, the Analytic Computing group plays an active role in

1. undertaking the task of developing a sophisticated liver cancer knowledge graph, integrating clinical data, medical expert domain knowledge, and In Silico data to have a unified and comprehensive understanding of liver cancer,
2. developing hybrid machine learning models to enhance liver cancer diagnosis and treatment. These models learn graph representations in geometric spaces, enabling a deeper understanding of complex patterns and relationships in liver cancer data. By leveraging these representations and reasoning over them, the models offer valuable insights and treatment recommendations.

Operating Time: 2023 - 2026
Source of Funding: BMBF

Project Team

• Prof. Dr. Steffen Staab. Head of the Department for Analytic Computing (AC), Institute for Parallel and Distributed System, University of Stuttgart.
• Mojtaba Nayyeri. Department for Analytic Computing (AC), Institute for Parallel and Distributed System, University of Stuttgart.

Partners

• Institute of Mechanics, Structural Analysis and Dynamics (ISD), University of Stuttgart
• Institute for Theoretical Biology (ITB), Humboldt-University Berlin
• Institute for Parallel and Distributed Systems (IPVS), University of Stuttgart
• Department of General, Visceral and Vascular Surgery, Jena University Hospital (UKJ)