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The Helmholtz Information & Data Science School for Health (HIDSS4Health) is a collaborative effort involving three prestigious institutions: the Karlsruhe Institute of Technology (KIT), the German Cancer Research Center (DKFZ), and the University of Heidelberg. This partnership encompasses over 40 research groups, each contributing to a diverse range of research areas, providing an excellent foundation for addressing key challenges in the realm of healthcare.

Data scientists play a pivotal role in the shaping the future of healthcare, and the researchers and partners at HIDSS4Health are actively contributing to defining the future health trends.

Mission Statement

The aim of the school is to attract, promote and train the best young talents at the interface between data science and health-related applications. HIDSS4Health offers a structured doctoral training program embedded in a highly interdisciplinary research environment bringing together experts from the data and life sciences. The scientific curriculum is complemented by training measures that provide doctoral researchers with the key qualifications expected from future leaders in science and industry.

Research Areas

  • In Imaging and Diagnostics, machine and deep learning is employed to leverage the expanding and complex datasets produced by modern high-throughput technologies in medicine, biology, and health-related biotechnology. This endeavor comes with a set of diverse challenges, encompassing real-time requirements, the quantification of uncertainty and ambiguity in both imaging and omics data, and the pursuit of transparent decision-making processes.
  • In Surgery & Intervention 4.0, the emphasis is on the role of data science in robot- and computer-assisted surgery and interventions. This involves the creation and application of computational techniques for the planning and automation of examinations, surgeries, and interventions, as well as the development of intelligent assistive systems that collaborate with physicians.
  • In Models for Personalized Medicine, the focus is on integrating data-driven modeling, simulation, and visual exploration with first principles modeling. This encompasses the development of models suitable for real-time applications and patient models designed for interactive visualization. A wide range of data is considered, including text, time series, features extracted from images or omics data, in addition to conventional medical data such as lab results.



People from EMCL

  • Prof. Dr. Vincent Heuveline
  • Elaine Zaunseder
  • Alejandra Jayme