natural language processing (nlp) algorithm (Optum Inc)
90
Structured Review
Optum Inc
natural language processing (nlp) algorithm
Natural Language Processing (Nlp) Algorithm, supplied by Optum Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/natural+language+processing+(nlp)+algorithm/nlp+system/pm39864953-32-1-9
Average 90 stars, based on 1 article reviews
Natural Language Processing (Nlp) Algorithm, supplied by Optum Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/natural+language+processing+(nlp)+algorithm/nlp+system/pm39864953-32-1-9
Average 90 stars, based on 1 article reviews
natural language processing (nlp) algorithm - by Bioz Stars,
2026-09
90/100 stars
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other:Article Title: Kidney Failure Events, Cardiovascular Disease Events, and All-Cause Mortality in Patients with IgA Nephropathy in a Real-World Database Article Snippet: This was an observational, retrospective cohort study using Article Title: Real-world comparative effectiveness of sacubitril/valsartan versus RAS inhibition alone in patients with de novo heart failure. Article Snippet: LVEF data are provided through the advanced NLP algorithm in Article Title: Classifying Unstructured Text in Electronic Health Records for Mental Health Prediction Models: Large Language Model Evaluation Study. Article Snippet: A natural language processing (NLP) algorithm integrated into the Article Title: A cohort study of predictors of short-term nonfatal suicidal and self-harm events among individuals with mental health disorders treated in the emergency department. Article Snippet: Background: Patients presenting to emergency departments (EDs) for mental health problems have an elevated short-term risk of repeat ED visits, subsequent hospitalization, and suicide.. Objective: Use health records to identify predictors of nonfatal suicidal or self-harm events following emergency department visits of individuals with mental health disorders.. Methods: Electronic health record data from 2015 to 2022 were used to identify ED visits with mental health diagnoses for individuals 10 and older; extract 408 potential predictors including demographic, historical and baseline clinical characteristics from structured and unstructured data; and subsequent suicidal and self-harm events. Article Title: Distinguishing cardiac catheter ablation energy modalities by applying natural language processing to electronic health records. Article Snippet: Article Title: Real‐world comparative effectiveness of sacubitril/valsartan versus RAS inhibition alone in patients with de novo heart failure Article Snippet: LVEF data are provided through the advanced NLP algorithm in Article Title: Real-world comparative effectiveness of sacubitril/valsartan versus RAS inhibition alone in patients with de novo heart failure. Article Snippet: In addition to the data captured directly from the local EHR structured fields, data [such as left ventricular ejection fraction (LVEF)] are extracted from the electronic free-text clinical notes via a Extraction:Article Title: Validation of Non–Small Cell Lung Cancer Clinical Insights Using a Generalized Oncology Natural Language Processing Model Article Snippet: PURPOSE Limited studies have used natural language processing (NLP) in the context of non–small cell lung cancer (NSCLC).. This study aimed to validate the application of an NLP model to an NSCLC cohort by extracting NSCLC concepts from free-text medical notes and converting them to structured, interpretable data.. METHODS Patients with a lung neoplasm, NSCLC histology, and treatment information in their notes were selected from a repository of over 27 million patients. |