Our corpus consisted of a gold-labeled data set of 1,524 clinical notes from 124 patients with lung cancer treated with RT, manually annotated for Common Terminology Criteria for Adverse Events (CTCAE ...
Using nationwide electronic health record (EHR) and cancer registry data from the VA Corporate Data Warehouse, we developed and validated a rule-based NLP algorithm to extract oncologist-determined MM ...
Large language models, a form of artificial intelligence, are generating a lot of hype in healthcare circles, primarily because of their potential to transform and improve various aspects of ...
Language Resources and Evaluation, Vol. 52, No. 2 (Spring 2018), pp. 571-601 (31 pages) Quality annotated resources are essential for Natural Language Processing. The objective of this work is to ...
Verified Market Research® a leading provider of business intelligence and market analysis is thrilled to announce the release of its comprehensive and authoritative report on the, "Natural Language ...
In a recent article published in Translational Psychiatry, researchers performed a systemic review and meta-analysis of scientific papers using an artificial intelligence (AI)-based tool that uses ...
Natural language processing (NLP) and speech processing at RIT is a research-active area led by Dr. Cecilia Alm’s and Dr. Marcos Zampieri’s laboratories. The groups’ research projects, supported by ...
The best way for insurers to make sure they're in compliance with the mandates of risk adjustment is to use natural language processing for accurate documentation and auditing, according to Dr. Calum ...
Natural language processing (NLP) is one of the most important frontiers in software. The basic idea—how to consume and generate human language effectively—has been an ongoing effort since the dawn of ...
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