Literature DB >> 3931972

INTERNIST-I properties: representing common sense and good medical practice in a computerized medical knowledge base.

F E Masarie, R A Miller, J D Myers.   

Abstract

INTERNIST-I is an experimental diagnostic consultant program for use on clinically challenging cases in internal medicine. Properties are a part of the INTERNIST-I knowledge representation scheme which embody essential information about the medical facts contained in the knowledge base. Properties provide the INTERNIST-I program with a measure of common sense and encourage the program to follow good medical practice. Properties substantially influence the behavior of the INTERNIST-I diagnostic program during case analyses. This paper reviews the implementation and significance of properties.

Mesh:

Year:  1985        PMID: 3931972     DOI: 10.1016/0010-4809(85)90022-9

Source DB:  PubMed          Journal:  Comput Biomed Res        ISSN: 0010-4809


  7 in total

1.  Evaluation of long-term maintenance of a large medical knowledge base.

Authors:  D A Giuse; N B Giuse; R A Miller
Journal:  J Am Med Inform Assoc       Date:  1995 Sep-Oct       Impact factor: 4.497

Review 2.  Medical diagnostic decision support systems--past, present, and future: a threaded bibliography and brief commentary.

Authors:  R A Miller
Journal:  J Am Med Inform Assoc       Date:  1994 Jan-Feb       Impact factor: 4.497

3.  A rational reconstruction of INTERNIST-I using PROTEGE-II.

Authors:  M A Musen; J H Gennari; W W Wong
Journal:  Proc Annu Symp Comput Appl Med Care       Date:  1995

4.  Comparing contents of a knowledge base to traditional information sources.

Authors:  N B Giuse; D A Giuse; R A Bankowitz; R A Miller
Journal:  Proc Annu Symp Comput Appl Med Care       Date:  1993

5.  Breast cancer risk estimation with artificial neural networks revisited: discrimination and calibration.

Authors:  Turgay Ayer; Oguzhan Alagoz; Jagpreet Chhatwal; Jude W Shavlik; Charles E Kahn; Elizabeth S Burnside
Journal:  Cancer       Date:  2010-07-15       Impact factor: 6.860

6.  Will machine learning end the viability of radiology as a thriving medical specialty?

Authors:  Stephen Chan; Eliot L Siegel
Journal:  Br J Radiol       Date:  2018-11-01       Impact factor: 3.039

7.  The INTERNIST-1/QUICK MEDICAL REFERENCE project--status report.

Authors:  R A Miller; M A McNeil; S M Challinor; F E Masarie; J D Myers
Journal:  West J Med       Date:  1986-12
  7 in total

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