Natural language generation in health care.

Good communication is vital in health care, both among health care professionals, and between health care 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, organization 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.

[1]  P. Ley,et al.  Communicating with Patients: Improving Communication, Satisfaction and Compliance , 1988 .

[2]  S. Banbury,et al.  What do patients want to know: An empirical approach to explanation generation and validation , 1995 .

[3]  J. Brug,et al.  The impact of a computer-tailored nutrition intervention. , 1996, Preventive medicine.

[4]  Lawrence M. Fagan,et al.  A therapy planning architecture that combines decision theory and artificial intelligence techniques. , 1990, Computers and biomedical research, an international journal.

[5]  W R Marshall,et al.  The efficacy of personalized audiovisual patient-education materials. , 1984, The Journal of family practice.

[6]  Chris Mellish,et al.  Optimizing the Costs and Benefits of Natural Language Generation , 1993, International Joint Conference on Artificial Intelligence.

[7]  Lewin Hc HF-Explain: a natural language generation system for explaining a medical expert system. , 1991 .

[8]  J Starren,et al.  Description generation of abnormal densities found in radiographs. , 1995, Proceedings. Symposium on Computer Applications in Medical Care.

[9]  Johanna D. Moore,et al.  An intelligent interactive system for delivering individualized information to patients , 1995, Artif. Intell. Medicine.

[10]  J. H. Hohnloser,et al.  Writing the Discharge Summary: A Cost Performance Analysis Using a Computerized Patient Record System , 1995 .

[11]  Ross D. Shachter,et al.  Patient-specific explanation in models of chronic disease , 1992, Artif. Intell. Medicine.

[12]  Diana E. Forsythe,et al.  Using ethnography in the design of an explanation system , 1995 .

[13]  J Pearson,et al.  Information for patients with cancer. Does personalization make a difference? Pilot study results and randomised trial in progress. , 1996, Proceedings : a conference of the American Medical Informatics Association. AMIA Fall Symposium.

[14]  Kathleen McKeown,et al.  Text generation: using discourse strategies and focus constraints to generate natural language text , 1985 .

[15]  A Hasman,et al.  Appraisal of computerized medical histories: comparisons between computerized and conventional records. , 1986, Computers and biomedical research, an international journal.

[16]  R. Jones,et al.  Use of a community-based touch-screen public-access health information system. , 1993, Health bulletin.

[17]  C. P. Langlotz A Decision-theoretic approach to heuristic planning , 1989 .

[18]  Marion J. Ball,et al.  Aspects of the Computer-based Patient Record , 1992, Computers in Health Care.

[19]  J. G. Douglas,et al.  Reducing hospital admission through computer supported education for asthma patients , 1994, BMJ.

[20]  Graeme Hirst,et al.  Authoring and Generating Health-Education Documents That Are Tailored to the Needs of the Individual Patient , 1997 .

[21]  L M Fagan,et al.  A computer-based tool for generation of progress notes. , 1993, Proceedings. Symposium on Computer Applications in Medical Care.

[22]  Steven K. Feiner,et al.  MAGIC: an experimental system for generating multimedia briefings about post-bypass patient status. , 1996, Proceedings : a conference of the American Medical Informatics Association. AMIA Fall Symposium.

[23]  Mediating hearer's and speaker's view in the generation of adaptive explanations , 1995 .

[24]  Holly Brügge Jimison,et al.  Generating explanations of decision models based on an augmented representation of uncertainty , 1988, UAI.

[25]  A. Cawsey Book Reviews: Participating in Explanatory Dialogues: Interpreting and Responding to Questions in Context , 1995, CL.

[26]  Michael Elhadad,et al.  Using argumentation to control lexical choice: a functional unification implementation , 1993 .

[27]  Johanna D. Moore,et al.  Generating explanations in context , 1993, IUI '93.

[28]  Carol Friedman,et al.  Medical text processing: past achievements, future directions , 1992 .

[29]  Sandra Carberry,et al.  Generating Coherent Messages in Real-time Decision Support: Exploiting Discourse Theory for Discourse Practice , 1997, ArXiv.

[30]  G O Barnett,et al.  An architecture for a distributed guideline server. , 1995, Proceedings. Symposium on Computer Applications in Medical Care.

[31]  Bonnie L. Webber,et al.  Upholding the Maxim of Relevance during Patient-Centered Activities , 1994, ANLP.

[32]  A. Rector,et al.  Foundations for an Electronic Medical Record , 1991, Methods of Information in Medicine.

[33]  Floriana Grasso,et al.  Generating recipient-centered explanations about drug prescription , 1996, Artif. Intell. Medicine.

[34]  H. Dobson,et al.  Tailored Written Invitations for Second round Breast Cancer Screening: A Randomised Controlled Trial , 1994, Journal of medical screening.

[35]  V. Strecher,et al.  The effects of computer-tailored smoking cessation messages in family practice settings. , 1994, The Journal of family practice.

[36]  Ehud Reiter,et al.  Has a Consensus NL Generation Architecture Appeared, and is it Psycholinguistically Plausible? , 1994, INLG.

[37]  D. Lindberg,et al.  Unified Medical Language System , 2020, Definitions.

[38]  J. D. Moore,et al.  Using the UMLS Semantic Network as a basis for constructing a terminological knowledge base: a preliminary report. , 1993, Proceedings. Symposium on Computer Applications in Medical Care.

[39]  J R Scherrer,et al.  Multilingual natural language generation as part of a medical terminology server. , 1995, Medinfo. MEDINFO.

[40]  D P Pretschner,et al.  An interactive report generator for bone scan studies. , 1991, Proceedings. Symposium on Computer Applications in Medical Care.

[41]  D L Schriger,et al.  The impact of a guideline-driven computer charting system on the emergency care of patients with acute low back pain. , 1995, Proceedings. Symposium on Computer Applications in Medical Care.

[42]  Byron E. Bork,et al.  Medical Records, Medical Education, and Patient Care , 1975 .

[43]  Bonnie L. Webber,et al.  Flexible support for trauma management through goal-directed reasoning and planning , 1992, Artif. Intell. Medicine.

[44]  Lawrence M. Fagan,et al.  A Methodology for Generating Computer-based Explanations of Decision-theoretic Advice , 1988, Medical decision making : an international journal of the Society for Medical Decision Making.

[45]  William R. Swartout,et al.  Explaining and Justifying Expert Consulting Programs , 1981, IJCAI.

[46]  I J Haimowitz Modeling all dialogue system participants to generate empathetic responses. , 1991, Computer methods and programs in biomedicine.