Pattern recognition applied to surgery

Features in a feature vector are defined in the conventional pattern recognition manner, but classes are defined interactively by the user as regions in the feature vector space. By storing training samples, where a sample is a feature vector, the class conditional probability density is estimated....

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Bibliographic Details
Published inComputers in biology and medicine Vol. 4; no. 3; pp. 293 - 300
Main Authors Patrick, Edward A., Stelmack, Frank, Panda, Durga P., Jardina, Steve
Format Journal Article
LanguageEnglish
Published United States Elsevier Ltd 01.02.1975
Subjects
Class conditional probability
Computers
Humans
Information Systems
Interactive
Medical
Pattern recognition
Pattern Recognition, Automated
Probability
Surgery
Surgical Procedures, Operative - classification
Computers
Medical
Pattern recognition
Class conditional probability
Surgery
Interactive
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Summary:Features in a feature vector are defined in the conventional pattern recognition manner, but classes are defined interactively by the user as regions in the feature vector space. By storing training samples, where a sample is a feature vector, the class conditional probability density is estimated. The procedure is applied to surgical patient features, the features corresponding to the kind of operation, diagnosis, patient's age, patient's sex, etc. A class is then a patient in a specific age group, of a specific sex, and with a specific diagnosis. The procedure is useful for determining numbers of particular kinds of operations and diagnoses, numbers of particular kinds of operations performed by a certain physician, etc.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:0010-4825
1879-0534
DOI:10.1016/0010-4825(75)90040-2