AIMC Topic: Natural Language Processing

Clear Filters Showing 3611 to 3620 of 3983 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
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.

Natural Language Processing for the Identification of Surgical Site Infections in Orthopaedics.

The Journal of bone and joint surgery. American volume
BACKGROUND: The identification of surgical site infections for infection surveillance in hospitals depends on the manual abstraction of medical records and, for research purposes, depends mainly on the use of administrative or claims data. The object...

Deep Learning on Big, Sparse, Behavioral Data.

Big data
The outstanding performance of deep learning (DL) for computer vision and natural language processing has fueled increased interest in applying these algorithms more broadly in both research and practice. This study investigates the application of DL...

Deep neural networks ensemble for detecting medication mentions in tweets.

Journal of the American Medical Informatics Association : JAMIA
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
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
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
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...

Neural machine translation of clinical texts between long distance languages.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: To analyze techniques for machine translation of electronic health records (EHRs) between long distance languages, using Basque and Spanish as a reference. We studied distinct configurations of neural machine translation systems and used d...

FP2VEC: a new molecular featurizer for learning molecular properties.

Bioinformatics (Oxford, England)
MOTIVATION: One of the most successful methods for predicting the properties of chemical compounds is the quantitative structure-activity relationship (QSAR) methods. The prediction accuracy of QSAR models has recently been greatly improved by employ...

Use of Natural Language Processing Algorithms to Identify Common Data Elements in Operative Notes for Total Hip Arthroplasty.

The Journal of bone and joint surgery. American volume
BACKGROUND: Manual chart review is labor-intensive and requires specialized knowledge possessed by highly trained medical professionals. Natural language processing (NLP) tools are distinctive in their ability to extract critical information from raw...