New Machine Learning-Driven Approaches for Peptide Hormone and Drug Discovery

Towards Theoretically Grounded Domain Adaptation for Brain Image Segmentation

New Methods for Functional Data to Quantify Clinically Relevant Traits of CGM (Continuous Glucose Monitor) Measurement Patterns and Guide Clinical Decision Making

Diffusion Models for Image Segmentation

Modelling Electrophysiological Features of Sleep and the Variation Induced by Differences in Species, Gender, Age, or Disease Using Deep Learning

The Impact of Genetic and Environmental Heterogeneity on Health Prediction Models

Improving the Clinical Utility of Prognostic Tools through Calibration

Increasing Predictive Performance and Generalizability of AI in Healthcare Using Meta-learning and Federated Learning in an International Collaboration

Tensor Networks for Efficient Image Rendering

Resolving Insulin Resistance Heterogeneity in Human Skeletal Muscle Using Multimodal Single-nucleus Sequencing