11 citations · 13 across the 3 of their papers we have counts for
3 papers
Bridging the Generalization Gap: Training Robust Models on Confounded Biological Data
Tzu-Yu Liu, Ajay Kannan, Adam Drake +2
Statistical learning on biological data can be challenging due to confounding variables in sample collection and processing. Confounders can cause models to generalize poorly and r…
METCC: METric learning for Confounder Control Making distance matter in high dimensional biological analysis
Kabir Manghnani, Adam Drake, Nathan Wan +1
High-dimensional data acquired from biological experiments such as next generation sequencing are subject to a number of confounding effects. These effects include both technical e…
Speech recognition for medical conversations
Chung-Cheng Chiu, Anshuman Tripathi, Katherine Chou +11
In this work we explored building automatic speech recognition models for transcribing doctor patient conversation. We collected a large scale dataset of clinical conversations ($1…