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   +(36) 88 624 023 |    dekanititkarsag@mik.uni-pannon.hu |    H-8200, Veszprem, Egyetem str. 10, Building I.

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News

Graduation Ceremony 2024 Summer

The Graduation Ceremony of the Faculty of Information Technology of the University of Pannonia will be held on 3rd July 2024 at 11:00 am.

Fill the survey and join to the University of Pannonia’s new alumni network!

In a bid to strengthen ties between past and present students, University of Pannonia is reinventing its international alumni network. This initiative aims to create a platform for networking, mentorship, and professional development.

Intensive incubation program

Join the 3 month intensive incubation program and launch your startup journey!

EUMaster4HPC : Call for applications for the next generation of European experts in supercomputing

Students can now apply to EUMaster4HPC, the first pan-European Master programme in High Performance Computing (HPC).Through online and on-site courses, leading European specialists in HPC are training the next generation of supercomputing experts.

Advanced Nonlinear Control Methods: Theory and applications (PhD Course)

The aim of this condensed 4-day PhD course is to introduce basic notions in nonlinear systems and control to interested students.

Head of the Centre: Ágnes Vathy-Fogarassy, Associate Professor

Email: vathy.agnes@mik.uni-pannon.hu

The most important medical data sources (e.g., hospital information systems, GP information systems, registers, national financial databases) store a huge amount data about medical treatments of the whole population. However, the information contained in these databases is often unexploited, and their use is usually limited to the retrospective and prospective collection of data, to the utilization in the operational patient care processes, and production of basic statistical analysis.

The goal of our research and development center is to perform healthcare analyses, develop optimized solutions and healthcare information systems, which are based on the exploitation of the healthcare data assets. To explore the knowledge in the data, we use the most dynamically developing discipline of information technology, namely the data science and the toolkit provided by the operations research.

During our researches, we develop a number of healthcare-specific methods and algorithms that implement effective information exploration and optimization adapted to healthcare. The applied data mining, network analysis, process mining, statistics, machine learning, deep learning algorithms and related visualization techniques can effectively help doctors and researchers discover relationships and patterns that are specific to patients, health care or diseases, and to prove or reject hypotheses. Furthermore, the healthcare sector offers optimization opportunities at many points when tested by formal means. Thus, by examining healthcare processes with the help of mathematically precise integer and mixed-integer models, optimal scenarios and bottlenecks of the system can be identified, providing improving steps.

The continuous cooperation of the healthcare specialists (physician, research physician) and IT specialist (data scientist) is an important basis for our activity. During our researches, we work closely together with the specialists of different research directions, who play an important role in defining the directions of researches, validating results and designating application areas.

R&D activities:

  • data mining analysis of healthcare data
  • IT support for personalized medical care
  • Development of intelligent medical decision support systems

Main applications and research areas:

  • Performing basic statistical analyses (calculation of population-level statistical indicators, incidence analyses, analysis of waiting and sojourn times, etc.)
  • Retrospective exploration of healthcare processes:
    • exploration of typical treatment patterns
    • identification of treatment deviations
    • certification of protocol tracking
  • Optimization of healthcare treatment processes:
    • identification of bottlenecks of medical care
    • proposal of optimized treatment processes
    • adapting graph theory framework to optimization methodologies in healthcare data under uncertainties
  • Development of optimized healthcare decision support systems
  • Complication assessment:
    • incidence analyses of complication assessment
    • identification of risk factors
    • development of scoring systems
  • Survival analysis
  • Correlation studies
  • Efficiency studies
  • Selection of control groups for retrospective case studies 

Connecting projects:

  • Development of intelligent and inclusive health information and decision support framework (2014 – 2017)
  • Development of intelligent cardiological process-based decision support system (2016 September – 2021 January)
  • Collaborative Hospital Information Platform: creating a medical system to support process-oriented inpatient care (2021-2024)

Partners:

  • National Healthcare Services Centre
  • GE Healthcare
  • Asseco Central Europe Magyarország Zrt.
  • Ferenc Csolnoky Hospital
  • State Hospital for Cardiology