Search Results for author: David Buckeridge

Found 8 papers, 5 papers with code

MixEHR-Nest: Identifying Subphenotypes within Electronic Health Records through Hierarchical Guided-Topic Modeling

1 code implementation17 Oct 2024 Ruohan Wang, Zilong Wang, Ziyang Song, David Buckeridge, Yue Li

Specifically, MixEHR-Nest detects multiple subtopics from each phenotype topic, whose prior is guided by the expert-curated phenotype concepts such as Phenotype Codes (PheCodes) or Clinical Classification Software (CCS) codes.

TrajGPT: Irregular Time-Series Representation Learning for Health Trajectory Analysis

no code implementations3 Oct 2024 Ziyang Song, Qingcheng Lu, He Zhu, David Buckeridge, Yue Li

In many domains, such as healthcare, time-series data is often irregularly sampled with varying intervals between observations.

Irregular Time Series Phenotype classification +3

Bidirectional Generative Pre-training for Improving Healthcare Time-series Representation Learning

1 code implementation14 Feb 2024 Ziyang Song, Qincheng Lu, He Zhu, David Buckeridge, Yue Li

Learning time-series representations for discriminative tasks, such as classification and regression, has been a long-standing challenge in the healthcare domain.

Prediction Representation Learning +1

BAND: Biomedical Alert News Dataset

1 code implementation23 May 2023 Zihao Fu, Meiru Zhang, Zaiqiao Meng, Yannan Shen, David Buckeridge, Nigel Collier

Infectious disease outbreaks continue to pose a significant threat to human health and well-being.

Epidemiology named-entity-recognition +3

Supervised multi-specialist topic model with applications on large-scale electronic health record data

1 code implementation4 May 2021 Ziyang Song, Xavier Sumba Toral, Yixin Xu, Aihua Liu, Liming Guo, Guido Powell, Aman Verma, David Buckeridge, Ariane Marelli, Yue Li

Motivation: Electronic health record (EHR) data provides a new venue to elucidate disease comorbidities and latent phenotypes for precision medicine.

Diagnostic Prediction +1

Predicting Infectiousness for Proactive Contact Tracing

1 code implementation ICLR 2021 Yoshua Bengio, Prateek Gupta, Tegan Maharaj, Nasim Rahaman, Martin Weiss, Tristan Deleu, Eilif Muller, Meng Qu, Victor Schmidt, Pierre-Luc St-Charles, Hannah Alsdurf, Olexa Bilanuik, David Buckeridge, Gáetan Marceau Caron, Pierre-Luc Carrier, Joumana Ghosn, Satya Ortiz-Gagne, Chris Pal, Irina Rish, Bernhard Schölkopf, Abhinav Sharma, Jian Tang, Andrew Williams

Predictions are used to provide personalized recommendations to the individual via an app, as well as to send anonymized messages to the individual's contacts, who use this information to better predict their own infectiousness, an approach we call proactive contact tracing (PCT).

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