Natural Language Generation in Healthcare: Brief Review
Alison J. Cawsey, Bonnie L. Webber, Ray B. Jones
Abstract
Good communication is vital in healthcare, both among healthcare professionals, and between healthcare professionals and their patients. And well-written documents, describing and/or explaining the information in structured databases may be easier to comprehend, more edifying and even more convincing, than the structured data, even when presented in tabular or graphic form. Documents may be automatically generated from structured data, using techniques from the field of natural language generation. These techniques are concerned with how the content, organisation and language used in a document can be dynamically selected, depending on the audience and context. They have been used to generate health education materials, explanations and critiques in decision support systems, and medical reports and progress notes.
Create a lesson
Related papers
A Memory-Based Approach to Learning Shallow Natural Language Patterns
Shlomo Argamon, Ido Dagan, Yuval Krymolowski
A Comparison of WordNet and Roget's Taxonomy for Measuring Semantic Similarity
Michael Mc Hale
Some Ontological Principles for Designing Upper Level Lexical Resources
Nicola Guarino
Towards an implementable dependency grammar
Timo Jarvinen, Pasi Tapanainen
A Variant of Earley Parsing
Mark-Jan Nederhof, Giorgio Satta
Segregatory Coordination and Ellipsis in Text Generation
James Shaw