102 citations · 471 across the 15 of their papers we have counts for
11 papers · 1 filter
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…
TransINT: Embedding Implication Rules in Knowledge Graphs with Isomorphic Intersections of Linear Subspaces
So Yeon Min, Preethi Raghavan, Peter Szolovits
Knowledge Graphs (KG), composed of entities and relations, provide a structured representation of knowledge. For easy access to statistical approaches on relational data, multiple…
Expert-Supervised Reinforcement Learning for Offline Policy Learning and Evaluation
Aaron Sonabend-W, Junwei Lu, Leo A. Celi +2
Offline Reinforcement Learning (RL) is a promising approach for learning optimal policies in environments where direct exploration is expensive or unfeasible. However, the adoption…
Representation Learning for Electronic Health Records
Wei-Hung Weng, Peter Szolovits
Information in electronic health records (EHR), such as clinical narratives, examination reports, lab measurements, demographics, and other patient encounter entries, can be transf…
Predicting Blood Pressure Response to Fluid Bolus Therapy Using Attention-Based Neural Networks for Clinical Interpretability
Uma M. Girkar, Ryo Uchimido, Li-wei H. Lehman +3
Determining whether hypotensive patients in intensive care units (ICUs) should receive fluid bolus therapy (FBT) has been an extremely challenging task for intensive care physician…
Unsupervised Multimodal Representation Learning across Medical Images and Reports
Tzu-Ming Harry Hsu, Wei-Hung Weng, Willie Boag +2
Joint embeddings between medical imaging modalities and associated radiology reports have the potential to offer significant benefits to the clinical community, ranging from cross-…