BACKGROUND: An accurate medication history, foundational for providing quality medical care, requires understanding of medication change events documented in clinical notes. However, extracting medication changes without the necessary clinical contex...
BACKGROUND AND OBJECTIVES: Clinical registries are critical for modern surgery and underpin outcomes research, device monitoring, and trial development. However, existing approaches to registry construction are labor-intensive, costly, and prone to m...
The missing data mechanism is a relevant problem in Machine Learning (ML) and biomedical informatics communities. Real-world Electronic Health Record (EHR) datasets comprise several missing values, thus revealing a high level of spatiotemporal sparsi...
Journal of the American Heart Association
Jun 22, 2023
Background The Fontan operation is associated with significant morbidity and premature mortality. Fontan cases cannot always be identified by () codes, making it challenging to create large Fontan patient cohorts. We sought to develop natural langua...
Suicide risk prediction models frequently rely on structured electronic health record (EHR) data, including patient demographics and health care usage variables. Unstructured EHR data, such as clinical notes, may improve predictive accuracy by allow...
INTRODUCTION: Weight gain among young adults continues to increase. Identifying adults at high risk for weight gain and intervening before they gain weight could have a major public health impact. Our objective was to develop and test electronic heal...
This paper describes contextualized medication event extraction for automatically identifying medication change events with their contexts from clinical notes. The striding named entity recognition (NER) model extracts medication name spans from an i...
Physicians make critical time-constrained decisions every day. Clinical predictive models can help physicians and administrators make decisions by forecasting clinical and operational events. Existing structured data-based clinical predictive models ...
International journal of medical informatics
Jun 5, 2023
OBJECTIVE: The objective of this study is to validate and report on portability and generalizability of a Natural Language Processing (NLP) method to extract individual social factors from clinical notes, which was originally developed at a different...
OBJECTIVE: To determine whether graph neural network based models of electronic health records can predict specialty consultation care needs for endocrinology and hematology more accurately than the standard of care checklists and other conventional ...