AIMC Journal:
Journal of the American Medical Informatics Association : JAMIA
Showing 391 to 400 of 493 articles
A study of deep learning approaches for medication and adverse drug event extraction from clinical text.
Journal of the American Medical Informatics Association : JAMIA
Jan 1, 2020
OBJECTIVE: This article presents our approaches to extraction of medications and associated adverse drug events (ADEs) from clinical documents, which is the second track of the 2018 National NLP Clinical Challenges (n2c2) shared task.
Using convolutional neural networks to identify patient safety incident reports by type and severity.
Journal of the American Medical Informatics Association : JAMIA
Dec 1, 2019
OBJECTIVE: To evaluate the feasibility of a convolutional neural network (CNN) with word embedding to identify the type and severity of patient safety incident reports.
Predicting emergency department orders with multilabel machine learning techniques and simulating effects on length of stay.
Journal of the American Medical Informatics Association : JAMIA
Dec 1, 2019
OBJECTIVE: Emergency departments (EDs) continue to pursue optimal patient flow without sacrificing quality of care. The speed with which a healthcare provider receives pertinent information, such as results from clinical orders, can impact flow. We s...
Deep neural networks ensemble for detecting medication mentions in tweets.
Journal of the American Medical Informatics Association : JAMIA
Dec 1, 2019
OBJECTIVE: Twitter posts are now recognized as an important source of patient-generated data, providing unique insights into population health. A fundamental step toward incorporating Twitter data in pharmacoepidemiologic research is to automatically...
Traditional Chinese medicine clinical records classification with BERT and domain specific corpora.
Journal of the American Medical Informatics Association : JAMIA
Dec 1, 2019
Traditional Chinese Medicine (TCM) has been developed for several thousand years and plays a significant role in health care for Chinese people. This paper studies the problem of classifying TCM clinical records into 5 main disease categories in TCM....
Extracting entities with attributes in clinical text via joint deep learning.
Journal of the American Medical Informatics Association : JAMIA
Dec 1, 2019
OBJECTIVE: Extracting clinical entities and their attributes is a fundamental task of natural language processing (NLP) in the medical domain. This task is typically recognized as 2 sequential subtasks in a pipeline, clinical entity or attribute reco...
Detecting conversation topics in primary care office visits from transcripts of patient-provider interactions.
Journal of the American Medical Informatics Association : JAMIA
Dec 1, 2019
OBJECTIVE: Amid electronic health records, laboratory tests, and other technology, office-based patient and provider communication is still the heart of primary medical care. Patients typically present multiple complaints, requiring physicians to dec...
What health records data are required for accurate prediction of suicidal behavior?
Journal of the American Medical Informatics Association : JAMIA
Dec 1, 2019
OBJECTIVE: The study sought to evaluate how availability of different types of health records data affect the accuracy of machine learning models predicting suicidal behavior.
Prognostic models will be victims of their own success, unless….
Journal of the American Medical Informatics Association : JAMIA
Dec 1, 2019
Predictive analytics have begun to change the workflows of healthcare by giving insight into our future health. Deploying prognostic models into clinical workflows should change behavior and motivate interventions that affect outcomes. As users respo...
Reducing drug prescription errors and adverse drug events by application of a probabilistic, machine-learning based clinical decision support system in an inpatient setting.
Journal of the American Medical Informatics Association : JAMIA
Dec 1, 2019
BACKGROUND: Drug prescription errors are made, worldwide, on a daily basis, resulting in a high burden of morbidity and mortality. Existing rule-based systems for prevention of such errors are unsuccessful and associated with substantial burden of fa...
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