Predicting disease onset from electronic health records for population health management: a scalable and explainable Deep Learning approach
R Grout, R Gupta, R Bryant, MA Elmahgoub… - Frontiers in Artificial …, 2024 - frontiersin.org
Introduction The move from a reactive model of care which treats conditions when they arise
to a proactive model which intervenes early to prevent adverse healthcare events will benefit …
to a proactive model which intervenes early to prevent adverse healthcare events will benefit …
Generic medical concept embedding and time decay for diverse patient outcome prediction tasks
Y Li, W Dong, B Ru, A Black, X Zhang, Y Guan - Iscience, 2022 - cell.com
Summary Many fields, including Natural Language Processing (NLP), have recently
witnessed the benefit of pre-training with large generic datasets to improve the accuracy of …
witnessed the benefit of pre-training with large generic datasets to improve the accuracy of …
LATTE: Label-efficient incident phenotyping from longitudinal electronic health records
Electronic health record (EHR) data are increasingly used to support real-world evidence
studies but are limited by the lack of precise timings of clinical events. Here, we propose a …
studies but are limited by the lack of precise timings of clinical events. Here, we propose a …
[HTML][HTML] Can Race-sensitive Biomedical Embeddings Improve Healthcare Predictive Models?
This reproducibility study presents an algorithm to weigh in race distribution data of clinical
research study samples when training biomedical embeddings. We extracted 12,864 …
research study samples when training biomedical embeddings. We extracted 12,864 …
Evaluation of Contextual and Non-contextual Word Embedding Models Using Radiology Reports
MS Khan - 2021 - search.proquest.com
Many clinical natural language processing (NLP) methods rely on non-contextual or
contextual word embedding models. Yet, few intrinsic evaluation benchmarks exist …
contextual word embedding models. Yet, few intrinsic evaluation benchmarks exist …