AIMC Topic: Electronic Health Records

Clear Filters Showing 2231 to 2240 of 2670 articles

[Automatic labeling and extraction of terms in natural language processing in acupuncture clinical literature].

Zhongguo zhen jiu = Chinese acupuncture & moxibustion
The paper analyzes the specificity of term recognition in acupuncture clinical literature and compares the advantages and disadvantages of three named entity recognition (NER) methods adopted in the field of traditional Chinese medicine. It is believ...

Ascertainment of Delirium Status Using Natural Language Processing From Electronic Health Records.

The journals of gerontology. Series A, Biological sciences and medical sciences
BACKGROUND: Delirium is underdiagnosed in clinical practice and is not routinely coded for billing. Manual chart review can be used to identify the occurrence of delirium; however, it is labor-intensive and impractical for large-scale studies. Natura...

Predicting Glaucoma Progression Requiring Surgery Using Clinical Free-Text Notes and Transfer Learning With Transformers.

Translational vision science & technology
PURPOSE: We evaluated the use of massive transformer-based language models to predict glaucoma progression requiring surgery using ophthalmology clinical notes from electronic health records (EHRs).

Automated Extraction of Pain Symptoms: A Natural Language Approach using Electronic Health Records.

Pain physician
BACKGROUND: Pain costs more than $600 billion annually and affects more than 100 million Americans, but is still a poorly understood problem and one for which there is very often limited effective treatment. Electronic health records (EHRs) are the o...

Automated information extraction from free-text medical documents for stroke key performance indicators: a pilot study.

Internal medicine journal
Automated information extraction might be able to assist with the collection of stroke key performance indicators (KPI). The feasibility of using natural language processing for classification-based KPI and datetime field extraction was assessed. Usi...

A Conceptual Framework to Predict Mental Health Patients' Zoning Classification.

Studies in health technology and informatics
Zoning classification is a rating mechanism, which uses a three-tier color coding to indicate perceived risk from the patients' conditions. It is a widely adopted manual system used across mental health settings, however it is time consuming and cost...

Application of Natural Language Processing to Learn Insights on the Clinician's Lived Experience of Electronic Health Records.

Studies in health technology and informatics
We interviewed six clinicians to learn about their lived experience using electronic health records (EHR, Allscripts users) using a semi-structured interview guide in an academic medical center in New York City from October to November 2016. Each par...

Entity recognition of Chinese medical text based on multi-head self-attention combined with BILSTM-CRF.

Mathematical biosciences and engineering : MBE
Named entities are the main carriers of relevant medical knowledge in Electronic Medical Records (EMR). Clinical electronic medical records lead to problems such as word segmentation ambiguity and polysemy due to the specificity of Chinese language s...

Artificial intelligence guided predicting the length of hospital-stay in a neurosurgical hospital based on the text data of electronic medical records.

Zhurnal voprosy neirokhirurgii imeni N. N. Burdenko
BACKGROUND: Rational use of internal resources of hospitals including bed fund turnover is important objective in high-tech medicine. Machine learning technologies can improve neurosurgical care and contribute to patient-oriented approach.