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QML4Med: Quantum computing meets machine learning in medicine

The QML4Med research project aims to explore the potential of the promising fusion of quantum computing and machine learning in a medical context. While machine learning is already established as a valuable tool in medicine, quantum computing is still at an early stage of development. This project is funded by FFG Österreichische Forschungsförderungsgesellschaft mbH.

Challenges in the integration of quantum computing in medicine

RISC Software GmbH will investigate three clinical use cases on simulated and real quantum hardware:

  1. 1. prediction of complications after blood transfusions
  2. 2. ECG diagnostics, e.g. detection of arrhythmias
  3. 3. pathology recognition from image data

The achieved model accuracies, the influence of noise, quantum coding methods and model explainability (explainable AI) are analyzed. QML4Med aims to identify promising categories of medical problems for quantum machine learning with quantum algorithms and hardware available in the medium term.

Long-term vision: management of future research and development activities

In the long term, QML4Med will significantly steer the direction of subsequent R&D&I activities, strengthen (supra)regional cooperation with industry and research and make a significant contribution to Austria’s technological sovereignty in the innovation field of quantum computing.

Schematic workflow in the QML4Med project

This project is funded by the FFG.

Project partners

Project details

  • Project short title: QML4Med
  • Project long title: Exploring the potential of quantum machine learning for personalized medical use cases
  • Call for proposals: Expedition Zukunft: Start, 2nd call for proposals – FFG
  • Project partners:
    • RISC Software GmbH
  • Funding call: FFG Basic Program
  • Term: 5/2024-4/2025 (12 months)
FFG project database

Ansprechperson









    Project management

    DI Philipp Moser, PhD

    Researcher & Developer

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