HealthDoc: Customizing patient information and health education by medical condition and personal characteristics. DiMarco, C.; Hirst, G.; Wanner, L.; and Wilkinson, J. In Workshop on Artificial Intelligence in Patient Education, Glasgow Scotland, August, 1995.
abstract   bibtex   
The HealthDoc project aims to provide a comprehensive approach to the customization of patient-information and health-education materials through the development of sophisticated natural language generation systems. We adopt a model of patient education that takes into account patient information ranging from simple medical data to complex cultural beliefs, so that our work provides both an impetus and testbed for research in multicultural health communication. We propose a model of language generation, `generation by selection and repair', that relies on a `master-document' representation that pre-determines the basic form and content of a text, yet is amenable to editing and revision for customization. The implementation of this model has so far led to the design of a sentence planner that integrates multiple complex planning tasks and a rich set of ontological and linguistic knowledge sources.
@InProceedings{	  dimarco2,
  author	= {Chrysanne DiMarco and Graeme Hirst and Leo Wanner and John
		  Wilkinson},
  title		= {HealthDoc: Customizing patient information and health
		  education by medical condition and personal
		  characteristics},
  booktitle	= {Workshop on Artificial Intelligence in Patient Education},
  address	= {Glasgow Scotland},
  month		= {August},
  year		= {1995},
  abstract	= {The HealthDoc project aims to provide a comprehensive
		  approach to the customization of patient-information and
		  health-education materials through the development of
		  sophisticated natural language generation systems. We adopt
		  a model of patient education that takes into account
		  patient information ranging from simple medical data to
		  complex cultural beliefs, so that our work provides both an
		  impetus and testbed for research in multicultural health
		  communication. We propose a model of language generation,
		  `generation by selection and repair', that relies on a
		  `master-document' representation that pre-determines the
		  basic form and content of a text, yet is amenable to
		  editing and revision for customization. The implementation
		  of this model has so far led to the design of a sentence
		  planner that integrates multiple complex planning tasks and
		  a rich set of ontological and linguistic knowledge
		  sources.},
  download	= {http://ftp.cs.toronto.edu/pub/gh/DiMarco++-HealthDoc-95.pdf}
		  
}
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