Article

Identifying Hepatocellular Carcinoma from imaging reports using natural language processing to facilitate data extraction from electronic patient records

2022-08-24

Abstract excerpt

<h4>Background</h4> The National Institute for Health Research Health Informatics Collaborative (NIHR HIC) viral hepatitis theme is working to overcome governance and data challenges to collate routine clinical data from electronic patients records from multiple UK hospital sites for translational research. The development of hepatocellular carcinoma (HCC) is a critical outcome for patients with viral hepatitis wi...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: ec32c595-0cb4-504f-8b32-5e90892b3e94
DOI: 10.1101/2022.08.23.22279119

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Identifying Hepatocellular Carcinoma from imaging reports using natural language processing to facilitate data extraction from electronic patient recordsDOI 10.1101/2022.08.23.22279119Read

Natural Language Processing for Clinical Laboratory Data Repository Systems: Implementation and Evaluation for Respiratory VirusesSemantic proximity Read

Natural Language Processing for the Ascertainment and Phenotyping of Left Ventricular Hypertrophy and Hypertrophic Cardiomyopathy on Echocardiogram ReportsSemantic proximity Read

Large language models for extracting histopathologic diagnoses of colorectal cancer and dysplasia from electronic health recordsSemantic proximity Read

ToKSA - Tokenized Key Sentence Annotation - a Novel Method for Rapid Approximation of Ground Truth for Natural Language ProcessingSemantic proximity Read

Augmented Intelligence with Natural Language Processing Applied to Electronic Health Records is Useful for Identifying Patients with Non-Alcoholic Fatty Liver Disease at Risk for Disease ProgressionSemantic proximity Read

A comparison of large language model versus manual chart review for extraction of data elements from the electronic health recordSemantic proximity Read

Data Extraction from Oncology Imaging Reports by Large Language Models: A Comparative Accuracy StudySemantic proximity Read

Large Language Model-Based Entity Extraction Reliably Classifies Pancreatic Cysts and Reveals Predictors of Malignancy: A Cross-Sectional and Retrospective Cohort StudySemantic proximity Read

Approach to Machine Learning for Extraction of Real-World Data Variables from Electronic Health RecordsSemantic proximity Read

General-purpose large language models can achieve physician-level accuracy in complex medical data extractionSemantic proximity Read

Improving Information Extraction from Pathology Reports using Named Entity RecognitionSemantic proximity Read

Systematic Review of Natural Language Processing Applied to Gastroenterology & Hepatology: The Current State of the ArtSemantic proximity Read