Diagnostik- und Forschungszentrum

RESEARCH FOCUS INFORMATION SCIENCE AND MACHINE LEARNING

Teamleader: Heimo Müller

Main Focus: The focus of our research group lies in the processing and analysis of data generated in the scientific and/or diagnostic process (focus: pathology). On the one hand, tools are developed, which make it possible to process data according to the FAIR principles and, on the other hand, existing algorithms (artificial intelligence) are analyzed and their explainability, including the human-machine interface, is presented and further developed (in cooperation with Andreas Holzinger). In the course of digitization, archive samples from the biobank are also being processed and made available in digital catalogs (in cooperation with Kurt Zatloukal).

Projekte

HEAP-Human Exposome Assessment Platform

  • The project creates a platform, which is a research resource for efficient analysis of the human exposome. One of the most significant outcomes is the knowledge that researchers consequently have obtained from cohort data, for example, in the context of cervical cancer screening. The platform that is being created here is set up in accordance with the FAIR principles (findable, accessible, interoperable and reusable) and ensures the sustainability of the formats, labeling and access procedures for data.
  • Duration of project: 2020-2024
  • Funded by: European Commission
  • Projectpartner: Karolinska Institutet, Statens Serum Institut (SSI), CSC-TIETEEN TIETOTEKNIIKAN KESKUS OY, LOGICAL CLOCKS AB, Stichting MLC Foundation, Uniwersytet Warszawski, European Science Infrastructure Services EEIG, CENTRE INTERNATIONAL DE RECHERCHE SUR LE CANCER, BOARD OF TRUSTEES OF THE LELAND STANFORD JUNIOR UNIVERSITY, Oulun Yliopisto, University of Innsbruck

AIDAVA

  • To make personal health data (PHD) interoperable, AI-enabled and reusable, the AIDAVA project wants to develop an AI-powered, virtual assistant (tested with hospitals) that maximizes the automation of data maintenance and allows the release of unstructured and structured, heterogeneous data. The virtual assistant includes a curation tool with AI-based personal data that users can access. The focus here is on the breast cancer patient register and longitudinal health records for cardiovascular patients. By increasing automation to improve data quality and deliver high-quality data, AIDAVA will reduce the workload of clinical data stewards, improve the effectiveness of clinical care, and support clinical research.
  • Duration of project: 2022-2026
  • Funded by: European Commission
  • Projectpartner: Universiteit Maastricht, b!loba, European Research and Project Office GmbH, Katholieke Universiteit Leuven, Sirma AI EAD, MIDATA Genossenschaft, The European Institute for Innovation through Health Data, Sihtasutus Pohja-Eesti Regionaalhaigla, Digi.me Limited, Gnome Design SRL, Averbis GmbH, European Cancer Patient Coalition, European Heart Network ASBL

Biobanking and the Cyprus Human Genome Project

  • Genetic testing of diseases and eHealth is a priority of the European project CY-Biobanking and can best be achieved through the creation of a Center of Excellence in Cyprus - as a contemporary biobank research infrastructure and modern research facility to support the project and promote the translat. research focused on genetic diseases. The project upgrades the existing infrastructure and implements high standard procedures and QMS to protect data and material of the highest reliability for later investigation.
  • Duration of project: 2019-2026
  • Funded by: European Commission
  • Project partner: University of Cyprus, BBMRI-ERIC, RTD Talos Limited

Smart FOX

  • Many clinical research activities in Austria face challenges due to non-linkable data sources. However, the true value of meaningful applications often lies in the networking of data. From an institutional perspective, analyzing data along a patient's continuous healthcare journey involving multiple healthcare providers creates blind spots and missing links. Smart FOX links ELGA-standardized health data with clinical registries for Colorectal Cancer and Heart Failure. This involves combining outpatient and inpatient data for the first time to investigate the continuum of healthcare and connecting biobanking infrastructures to ELGA-standardized health data donations in specific research contexts. Ultimately, Smart FOX will pave the way for citizen/patient-empowered data donation in Austria, democratizing and fully harnessing the potential of the data collected along the patient pathway to improve health outcomes, alleviate the burden on healthcare systems, and create new opportunities for the Austrian industry and will significantly improve Austria's readiness for the upcoming European Health Data Space.
  • Duration of the project: 2023-2025
  • Funded by: FFG
  • Projectpartner: AIT, GÖG, LBI DHPS, MUW, UMIT, UniVie, Dedalus, EIT, fragentiX, ITSV, Probando, SHS, TBM, LIV, DIO, Survivors AT

RI-Scale

  • The project will operate a distributed network of experts, a Competence Centre, through which the DEP (Data Exploitation Platform) technology will be designed, developed into a software prototype and related deployment-operational guides that enable RI (Research Infrastructures) data holdings to extend their portfolio with co-provisioned scalable compute services on e-infrastructures. Herein, datasets from the data holdings can be replicated and offered for data-intensive analysis. The DEP will implement trusted data replication and lifecycle management with energy-consumption minimisation across the overall transfer, compute and storage operational pipeline. The operation will be based on coherent identity management, authentication and authorisation solutions that ensure trust and interoperability across RIs, e-infrastructures and the emerging ecosystem of Data Spaces.
  • Duration of the project: 2025-2027
  • Funded by: EU
  • Projectpartner: Stichting EGI, Masarykova Univerzita, TU Wien, fragmentiX, BBMRI-ERIC, EMBL, CERN, MMCI, DKRZ, Universitat Politecnica de Valencia

BioMedAI Twinning

  • The increasing demand for sophisticated clinical diagnostics makes the current diagnostic capacities insufficient. Artificial Intelligence (AI) and machine learning seem to be very promising approaches to automate diagnostic systems. However, most academic AI systems are opaque black boxes that cannot be understood, tested, and certified without competent knowledge. This motivates Masaryk University and Masaryk Institute of Oncology to collaborate with two advanced partners, the Medical University of Graz and the Technical University of Berlin, and to build a BioMedAI infrastructure that enables close collaboration between computer scientists and clinical experts, reliable AI - to develop explainable solutions. The main part of the BioMedAI project focuses on the training of computer science researchers at the MU and clinical experts at the MMCI in the development of explainable AI methods, validated on medical data basis and in a clinical setting.
  • Duration of project: 2022-2025
  • Funded by: European Commission
  • Projectpartner: Masarykova Univerzita, Technische Universität Berlin, Masarykuv Onkologicky Ustav

ONCOSCREEN

  • With colorectal cancer (CRC) accounting for 12.4% of all cancer-related deaths and only 14% of EU citizens participating in screening programmes, there is an urgent need for accurate, non-invasive, inexpensive screening tests based on novel ones technologies and increased awareness of the disease and its detection. In addition, personalized approaches to screening are needed to account for genetic and other socioeconomic variables and environmental stressors. ONCOSCREEN responds to these challenges by developing a population-level risk-based stratification methodology for CRC to account for genetic prevalence, socioeconomic status, and other factors. The project is supported by a multidisciplinary consortium of 38 partners, including technical solution providers, hospitals, health ministries as policy makers, legal and ethical experts, insurance companies, and the active involvement of end users/citizens through targeted workshops at all stages of implementation.
  • Duration of project: 2023-2026
  • Funded by: European Commission
  • Projectpartner: EXUS Software Monoprosopi Etairia Periorismenis Evthinis, Universitaetsmedizin Der Johannes Gutenberg-Universitaet Mainz, Institute Of Communication And Computer Systems, Firalis, Universitätsklinikum Schleswig-Holstein, Lietuvos Sveikatos Mokslu Universitetas, Technion – Israel Institute Of Technology, Time.Lex, Ethniko Kentro Erevnas Kai Technologikis Anaptyxis, CCASSURED, Universidad De La Rioja, Carr Communications Limited, Ministry Of Health- Greece, Medizinische Universität Innsbruck, Gercor a.o.

Diagnostic and Research Institute of Pathology

Dr.
Heimo Müller  
T: +43 316 385 71764