Clinical trial cohort selection based on multi-level rule-based natural language processing system

Bootstrapping Statistical Processing Into A Rule-Based Natural Language Parser

This paper describes a "bootstrapping" method which uses a broad-coverage, rule-based parser to compute probabilities while parsing an untagged corpus of NL text, and which then incorporates those probabilities into the processing of the same parser as it analyzes new text. Results are reported which show that this method can significantly improve the speed and accuracy of the parser without re...

A Rule-Based Expert System for Low Level Image Processing

Implementation Brief: Description of a Rule-based System for the i2b2 Challenge in Natural Language Processing for Clinical Data

The Obesity Challenge, sponsored by Informatics for Integrating Biology and the Bedside (i2b2), a National Center for Biomedical Computing, asked participants to build software systems that could "read" a patient's clinical discharge summary and replicate the judgments of physicians in evaluating presence or absence of obesity and 15 comorbidities. The authors describe their methodology and dis...

Natural language processing based automated system for UML diagrams generation

This paper presents a natural language processing based automated system for generating UML diagrams after analyzing the given business details in the form of the text. A new model is presented for analyzing the natural languages and extracting the relative and required information from the given storyline by the user. User writes the requirements in simple English in a few paragraphs and the d...

Development of Machine Learning based Natural Language Processing System

For disease diagnostic knowledge base system (including Q&A, consistency checker, and informativity checker) requiring higher degree of strictness on the results of a query to the system, at the development stage, great efforts are necessary to improve machine learning based statistical performance tests, measured by precision and recall rates, on the training error and prediction. Performance ...