- BabyNet++: Fetal Birth Weight Prediction using Biometry Multimodal Data Acquired Less Than 24 Hours Before Delivery
- Can gamification reduce the burden of self-reporting in mHealth applications? A feasibility study using machine learning from smartwatch data to estimate cognitive load
- Decoding Emotional Valence from Wearables: Can Our Data Reveal Our True Feelings?
- Designing Personalised Gamification of mHealth Survey Applications
- TabAttention: Learning Attention Conditionally on Tabular Data
- Multi-task Swin Transformer for Motion Artifacts Classification and Cardiac Magnetic Resonance Image Segmentation
- Artificial intelligence in the diagnosis of necrotising enterocolitis in newborns
- Cell image augmentation for classification task using GANs on Pap Smear Dataset
- BabyNet: Residual Transformer Module for Birth Weight Prediction on Fetal Ultrasound Video
- Estimation of the Impact of COVID-19 Pandemic Lockdowns on Breast Cancer Deaths and Costs in Poland using Markovian Monte Carlo Simulation
- Noninvasive Estimation of Mean Pulmonary Artery Pressure Using MRI, Computer Models, and Machine Learning
- Justifying Short-Term Load Forecasts Obtained with the Use of Neural Models
Research / Health Informatics Group at Sano (HIGS)
Michał Grzeszczyk
PhD Student in Health Informatics
Michał is PhD student who joins Health Informatics team and will work on Machine learning estimation of pulmonary circulation abnormalities using phase contrast MR and echocardiography. He is a graduate of Computer Science studies at the Warsaw University of Technology and Technical University of Berlin (dual-degree). At Sano he’ll be working on non-invasive pulmonary hypertension detection. He is passionate about utilizing of AI in various areas. After hours, he works with his friend on the mobile application Chefs’ which is devoted to storing and sharing cooking recipes coming from multiple sources like images or websites. In his free time he loves playing football and discovering new sport disciplines.