Areas of Scientific Interest
Digital pathology. Predictive models of disease. Medical informatics. Machine learning. AI solutions.
Main Activities / Research Directions
Consolidate the academic potential of digital medicine for artificial intelligence solutions:
- Facilitate interdisciplinary collaboration at Vilnius University and with external partners.
Develop training modules in health informatics.
Promote the development of digital medicine science and technology:
- Initiate potentially high-added-value projects by integrating multimodal data sets and improving their quality.
- Consult on aspects of health data management and use, initiating projects and participating in them, if necessary.
Develop niche technologies that can provide unique value to digital medicine models:
- Develop research on digital/computational biomarkers in pathology, radiology and other fields.
- Develop multimodal microscopy imaging technologies with a perspective for clinical application.
Research
PhD students:
Vygantė Maskoliūnaitė. Prognostic Modeling of Primary Cutaneous Melanoma by Digital Pathology and Machine Learning Methods (Academic supervisor: Prof. Dr. Arvydas Laurinavičius).
Mantas Fabijonavičius. Machine Learning-Driven Assessment of Renal Cancer Microenvironment for Prognostic Modeling (Academic supervisor: Prof. Dr. Arvydas Laurinavičius).
Renaldas Augulis. Artificial Intelligence-Enabled Kidney Histomorphometrics for Clinical and Experimental Research (Academic supervisor: Prof. Dr. Arvydas Laurinavičius).
Methods and Infrastructure Used
Leica Aperio virtual microscopy.
Polychromatic polarized microscopy.
HALO AP/ HALO AI image analysis platform.
Statistical analysis platform, SAS.
Computational platform, NVIDIA GPU.
Projects
Polychromatic Polarization Microscopy for Machine Learning in Tissue Pathology (PPM4ML), Lithuanian Research Council, Researcher groups project, 2024-2027.
Data Center for Machine Learning and Quantum Computing in Natural and Biomedical Sciences (Project no.: S-A-UAI-23-11)/MF involved in "Center of Excellence in Digital Medicine" (SMEC), LR budget (LMT, ŠMSM), 2023–2027.
Hexagonal Grid Analytics Technology Platform for Pathology (No. P-ITP-25-46) (Hex4Path), Research Council of Lithuania, Targeted Programme “Information Technologies for the Development of Science and the Knowledge Society”, Call II, 1 September 2025–31 August 2027.
Cooperation
Vilnius University Hospital Santaros klinikos.
Vilnius University Faculty of Physics.
Vilnius University Faculty of Mathematics and Informatics.
Lithuanian Association of Artificial Intelligence.
Marine Biological Laboratory.
University of Caen Normandy.
List of Employees and Contacts
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Academic degree |
Name |
Memberships in societies |
Contacts |
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Prof.
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Arvydas Laurinavičius (Head of Centre) |
ESDIP (Advisory Board)
Journal of Pathology Informatics (Editorial Board) |
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PhD
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PhD
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PhD
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PhD candidate |
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PhD candidate |
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Martynas Bieliauskas |
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PhD |
Julius Juodakis |
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PhD |
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PhD |
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Benoit Plancoulaine |
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PhD |
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PhD |
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| PhD | Ernesta Mačionienė | ||
| PhD | Agnė Kerpauskienė |
Information for Those Interested in Cooperation
Cooperation and Services: digital image analysis and analytics, biological tissue research, digital biomarkers, development and validation of predictive disease models, semantic and technical standards for health information systems, federated machine learning.
Keywords: digital pathology; digital microscopy technologies; image analysis; machine learning; predictive disease models; artificial intelligence systems; health informatics.
For cooperation and partnerships at the Translational Health Research Institute, please contact: