Text preprocessing for improving hypoglycemia detection from clinical notes–A case study of patients with diabetes

L Zhou, T Siddiqui, SL Seliger, JB Blumenthal… - International journal of …, 2019 - Elsevier
Background and objective Hypoglycemia is a common safety event when attempting to
optimize glycemic control in diabetes (DM). While electronic medical records provide a …

Ontology-based question understanding with the constraint of Spatio-temporal geological knowledge

W Li, L Wu, Z Xie, L Tao, K Zou, F Li, J Miao - Earth Science Informatics, 2019 - Springer
Spatio-temporal geological big data contain a large amount of spatial and nonspatial data. It
is important to effectively manage and retrieve these existing data for geological research …

Modeling heterogeneous clinical sequence data in semantic space for adverse drug event detection

A Henriksson, J Zhao, H Boström… - 2015 IEEE International …, 2015 - ieeexplore.ieee.org
The enormous amounts of data that are continuously recorded in electronic health record
systems offer ample opportunities for data science applications to improve healthcare. There …

Expansion of medical vocabularies using distributional semantics on Japanese patient blogs

M Ahltorp, M Skeppstedt, S Kitajima… - Journal of biomedical …, 2016 - Springer
Background Research on medical vocabulary expansion from large corpora has primarily
been conducted using text written in English or similar languages, due to a limited …

Temporal weighting of clinical events in electronic health records for pharmacovigilance

J Zhao - 2015 IEEE International Conference on Bioinformatics …, 2015 - ieeexplore.ieee.org
Electronic health records (EHRs) have recently been identified as a potentially valuable
source for monitoring adverse drug events (ADEs). However, ADEs are heavily under …

Machine Learning for Analyzing Drug Safety in Electronic Health Records

M Guan - Machine Learning and Deep Learning in …, 2023 - Springer
A large amount of patient harm is preventable with timely and accurate detection of adverse
drug events (ADEs). The ability to identify these events has been a challenge due to the …

MultiADE: A Multi-domain Benchmark for Adverse Drug Event Extraction

X Dai, S Karimi, A Sarker, B Hachey, C Paris - arXiv preprint arXiv …, 2024 - arxiv.org
Objective. Active adverse event surveillance monitors Adverse Drug Events (ADE) from
different data sources, such as electronic health records, medical literature, social media …

[HTML][HTML] Finding important terms for patients in their electronic health records: a learning-to-rank approach using expert annotations

J Chen, J Zheng, H Yu - JMIR medical informatics, 2016 - medinform.jmir.org
Background: Many health organizations allow patients to access their own electronic health
record (EHR) notes through online patient portals as a way to enhance patient-centered …

STO: Stroke Ontology for Accelerating Translational Stroke Research

M Habibi-Koolaee, L Shahmoradi… - Neurology and …, 2021 - Springer
Introduction Ontology-based annotation of evidence, using disease-specific ontologies, can
accelerate analysis and interpretation of the knowledge domain of diseases. Although many …

Distant supervision with transductive learning for adverse drug reaction identification from electronic medical records

S Taewijit, T Theeramunkong… - Journal of healthcare …, 2017 - Wiley Online Library
Information extraction and knowledge discovery regarding adverse drug reaction (ADR)
from large‐scale clinical texts are very useful and needy processes. Two major difficulties of …