Supervisor: Giacomo Cappon
Creation Date: 15/10/2026 08:59
The project will develop and evaluate explainable machine-learning models for breast cancer risk assessment using health registry and environmental data. The models will estimate individual risk and explain the main factors contributing to each prediction.
Dataset type: Already acquired data
Dataset description: Planned sources include Swedish cancer and healthcare registries, demographic and socioeconomic datasets, and environmental and climate data from SMHI.
List of Methods: Explainable AI, machine learning, cancer risk prediction, environmental exposures, data integration, model evaluation.