Literature DB >> 1254707

Computer-assisted bacterial identification utilizing antimicrobial susceptibility profiles generated by autobac 1.

B H Sielaff, E A Johnson, J M Matsen.   

Abstract

A computer program was developed to identify bacteria solely on the basis of their relative susceptibility to various antimicrobial agents. A sample of 481 clinical isolates from nine of the most commonly isolated gram-negative groups was identified by the quadratic discriminant function technique. Various combinations of antimicrobials were tried, and one set of 18 resulted in a more than 97% correlation with conventional identification procedures. The antimicrobial set could be decreased to 14, while a better than 95% correlation with the conventional procedures was maintained.

Mesh:

Year:  1976        PMID: 1254707      PMCID: PMC274243          DOI: 10.1128/jcm.3.2.105-109.1976

Source DB:  PubMed          Journal:  J Clin Microbiol        ISSN: 0095-1137            Impact factor:   5.948


  5 in total

1.  Laboratory data analysis system. IV. Multivariate diagnosis.

Authors:  R R Grams; E A Johnson; E S Benson
Journal:  Am J Clin Pathol       Date:  1972-08       Impact factor: 2.493

2.  Laboratory data analysis system. 3. Multivariate normality.

Authors:  R R Grams; E A Johnson; E S Benson
Journal:  Am J Clin Pathol       Date:  1972-08       Impact factor: 2.493

3.  Computer identification of bacteria on the basis of their antibiotic susceptibility patterns.

Authors:  R Friedman; J MacLowry
Journal:  Appl Microbiol       Date:  1973-09

4.  Antimicrobial susceptibility as a diagnostic aid in the identification of nonfermenting gram-negative bacteria.

Authors:  G L Gilardi
Journal:  Appl Microbiol       Date:  1971-11

5.  Antibiotic disc susceptibility tests for rapid presumptive identification of Gram-negative anaerobic bacilli.

Authors:  V L Sutter; S M Finegold
Journal:  Appl Microbiol       Date:  1971-01
  5 in total
  9 in total

1.  Biographical feature: John Matsen, M.D.

Authors:  Karen C Carroll
Journal:  J Clin Microbiol       Date:  2014-06-11       Impact factor: 5.948

2.  A collaborative evaluation of a rapid automated bacterial identification system: the Autobac IDX.

Authors:  M Stevens; R K Feltham; F Schneider; C Grasmick; F Schaak; P Roos
Journal:  Eur J Clin Microbiol       Date:  1984-10       Impact factor: 3.267

3.  Automated, rapid identification of bacteria by pattern analysis of growth inhibition profiles obtained with Autobac 1.

Authors:  G E Buck; B H Sielaff; R Boshard; J M Matsen
Journal:  J Clin Microbiol       Date:  1977-07       Impact factor: 5.948

4.  Accuracy and precision of the autobac system for rapid identification of Gram-negative bacilli: a collaborative evaluation.

Authors:  A L Barry; T L Gavan; P B Smith; J M Matsen; J A Morello; B H Sielaff
Journal:  J Clin Microbiol       Date:  1982-06       Impact factor: 5.948

5.  Novel approach to bacterial identification that uses the autobac system.

Authors:  B H Sielaff; J M Matsen; J E McKie
Journal:  J Clin Microbiol       Date:  1982-06       Impact factor: 5.948

Review 6.  A review of numerical methods in bacterial identification.

Authors:  W R Willcox; S P Lapage; B Holmes
Journal:  Antonie Van Leeuwenhoek       Date:  1980       Impact factor: 2.271

7.  Effect of atypical antibiotic resistance on microorganism identification by pattern recognition.

Authors:  J C Boyd; J W Lewis; J J Marr; A M Harper; B R Kowalski
Journal:  J Clin Microbiol       Date:  1978-12       Impact factor: 5.948

8.  Use of Autobac 1 for rapid assimilation testing of Candida and Torulopsis species.

Authors:  J H Ngui Yen; J A Smith
Journal:  J Clin Microbiol       Date:  1978-02       Impact factor: 5.948

9.  Host Taxon Predictor - A Tool for Predicting Taxon of the Host of a Newly Discovered Virus.

Authors:  Wojciech Gałan; Maciej Bąk; Małgorzata Jakubowska
Journal:  Sci Rep       Date:  2019-03-05       Impact factor: 4.379

  9 in total

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