33 citations · 102 across the 13 of their papers we have counts for
6 papers · 1 filter
Forecasting Emergency Department Capacity Constraints for COVID Isolation Beds
Erik Drysdale, Devin Singh, Anna Goldenberg
Predicting patient volumes in a hospital setting is a well-studied application of time series forecasting. Existing tools usually make forecasts at the daily or weekly level to ass…
Chasing Your Long Tails: Differentially Private Prediction in Health Care Settings
Vinith M. Suriyakumar, Nicolas Papernot, Anna Goldenberg +1
Machine learning models in health care are often deployed in settings where it is important to protect patient privacy. In such settings, methods for differentially private (DP) le…
Making Sense of the Robotized Pandemic Response: A Comparison of Global and Canadian Robot Deployments and Success Factors
T. Barfoot, J. Burgner-Kahrs, E. Diller +12
From disinfection and remote triage, to logistics and delivery, countries around the world are making use of robots to address the unique challenges presented by the COVID-19 pande…
A Comprehensive Evaluation of Multi-task Learning and Multi-task Pre-training on EHR Time-series Data
Matthew B. A. McDermott, Bret Nestor, Evan Kim +4
Multi-task learning (MTL) is a machine learning technique aiming to improve model performance by leveraging information across many tasks. It has been used extensively on various d…
Using Generative Models for Pediatric wbMRI
Alex Chang, Vinith M. Suriyakumar, Abhishek Moturu +3
Early detection of cancer is key to a good prognosis and requires frequent testing, especially in pediatrics. Whole-body magnetic resonance imaging (wbMRI) is an essential part of…
What went wrong and when? Instance-wise Feature Importance for Time-series Models
Sana Tonekaboni, Shalmali Joshi, Kieran Campbell +2
Explanations of time series models are useful for high stakes applications like healthcare but have received little attention in machine learning literature. We propose FIT, a fram…