Davin Hill

Unsupervised representation learning improves genomic discovery and risk prediction for respiratory and circulatory functions and diseases

This paper introduces a deep learning framework, REGLE, that improves genomic discovery and risk prediction for respiratory and circulatory diseases by learning low-dimensional embeddings from high-dimensional clinical data.

Leveraging deep-learning on raw spirograms to improve genetic understanding and risk scoring of COPD despite noisy labels

This paper trains a deep neural network on noisy COPD labels to predict COPD status from spirograms, improving genetic discovery by identifying new loci and replicating existing ones.