Aleksei Tiulpin's Intelligent Medical Systems Research Group
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About
Aleksei Tiulpin's research group develops AI methods for medical applications, focusing on disease prevention and integration into care pathways. Research interests include multimodal data, semi-supervised learning, uncertainty prediction, and human-AI interaction. The lab develops tools for medical image analysis, disease trajectory forecasting, and anatomical landmark localization using techniques like transformers, triplet loss, and deep ensembles. Specific applications include knee osteoarthritis diagnosis, brain tumor segmentation, and retinal image segmentation.
Platform
Task
Features
• multimodal data analysis
• machine learning for medical applications
• intelligent medical systems
• uncertainty-aware segmentation
• anatomical landmark localization
• knee osteoarthritis diagnosis
• medical image matching
• disease trajectory forecasting
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