Brett K. Beaulieu-Jones
Orcid: 0000-0002-6700-1468
According to our database1,
Brett K. Beaulieu-Jones
authored at least 18 papers
between 2016 and 2024.
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Bibliography
2024
Recent Advances, Applications, and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2023 Symposium.
CoRR, 2024
2023
Zero-shot interpretable phenotyping of postpartum hemorrhage using large language models.
npj Digit. Medicine, 2023
2021
Machine learning for patient risk stratification: standing on, or looking over, the shoulders of clinicians?
npj Digit. Medicine, 2021
Validation of an internationally derived patient severity phenotype to support COVID-19 analytics from electronic health record data.
J. Am. Medical Informatics Assoc., 2021
Innovative methodological approaches for data integration to derive patterns across diverse, large-scale biomedical datasets.
Proceedings of the Biocomputing 2021: Proceedings of the Pacific Symposium, 2021
2020
International electronic health record-derived COVID-19 clinical course profiles: the 4CE consortium.
npj Digit. Medicine, 2020
Proceedings of the Pacific Symposium on Biocomputing 2020, 2020
Proceedings of the Pacific Symposium on Biocomputing 2020, 2020
Regularization of Deep Neural Networks for EEG Seizure Detection to Mitigate Overfitting.
Proceedings of the 44th IEEE Annual Computers, Software, and Applications Conference, 2020
2019
Learning Contextual Hierarchical Structure of Medical Concepts with Poincairé Embeddings to Clarify Phenotypes.
Proceedings of the Biocomputing 2019: Proceedings of the Pacific Symposium, 2019
Machine Learning for Health ( ML4H ) 2019 : What Makes Machine Learning in Medicine Different?
Proceedings of the Machine Learning for Health Workshop, 2019
2018
Mapping patient trajectories using longitudinal extraction and deep learning in the MIMIC-III Critical Care Database.
Proceedings of the Biocomputing 2018: Proceedings of the Pacific Symposium, 2018
2017
Missing Data Imputation in the Electronic Health Record Using Deeply Learned Autoencoders.
Proceedings of the Biocomputing 2017: Proceedings of the Pacific Symposium, 2017
2016
Semi-supervised learning of the electronic health record for phenotype stratification.
J. Biomed. Informatics, 2016