Thesis supervisor: Gergely Fodor
Location of studies (in Hungarian): University of Szeged, Albert Szent-Györgyi Medical School, Dept. of Medical Physics and Informatics Abbreviation of location of studies: OFOII
Description of the research topic:
In the realm of life sciences, the integration of artificial intelligence (AI) offers unparalleled opportunities to revolutionize data analysis methodologies. This research program is dedicated to leveraging AI to enhance measurements and processing of biological data across diverse domains, with a particular focus on the analysis of results from respiratory measurements while exploring broader applications.
This proposed research program seeks to harness the power of AI to revolutionize the analysis of respiratory data, with an emphasis on enhancing our understanding of respiratory diseases and optimizing clinical management strategies. By employing advanced machine learning algorithms and data-driven techniques, researchers aim to aid data analysis and to uncover hidden patterns, biomarkers, and predictive models within data derived from animal models or human subjects. Beyond respiratory data, the program also aims to explore AI applications in other areas of life sciences, thereby fostering interdisciplinary collaborations and driving transformative discoveries.
Through interdisciplinary collaborations and a commitment to data-driven approaches, this research endeavour aims to accelerate scientific discovery and optimize data analysis methodologies across the life sciences spectrum. By harnessing the power of AI, we anticipate transformative insights that will not only deepen our understanding of biological systems but also drive innovation and pave the way for improved healthcare outcomes.
Required language skills: english Number of students who can be accepted: 1
Deadline for application: 2024-12-31
2024. IV. 17. ODT ülés Az ODT következő ülésére 2024. június 14-én, pénteken 10.00 órakor kerül sor a Semmelweis Egyetem Szenátusi termében (Bp. Üllői út 26. I. emelet).
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