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Tim Miller

Associate Professor

Computational Health Informatics Program
Boston, MA

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Semi-supervised Learning for Phenotyping Tasks

Semi-supervised Learning for Phenotyping Tasks

Dligach D, Miller T, Savova GK. Semi-supervised Learning for Phenotyping Tasks. In: AMIA Annual Symposium Proceedings. 2015.

Last updated on 02/25/2023

Recent Publications

A BERT-based Universal Model for Both Within- and Cross-sentence Clinical Temporal Relation Extraction
Cross-document coreference: An approach to capturing coreference without context
Extracting Adverse Drug Event Information with Minimal Engineering
Simplified Neural Unsupervised Domain Adaptation
Two-stage Federated Phenotyping and Patient Representation Learning
Unsupervised Learning of PCFGs with Normalizing Flow

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