Lykke Pedersen

New Results doi: https://doi.org/10.1101/2022.01.14.475226 Abstract The identification of predictive biomarker signatures from omics data for clinical applications is an active area of research. Recent developments in assay technologies and machine learning (ML) methods have led to significant improvements in predictive performance. However, most high-performing ML methods suffer from complex architectures and lack interpretability.