NATURAL LANGUAGE PROCESSING OF ELECTRONIC RECORDS

Electronic records are accessed from computer storage for a given subject, wherein the electronic records include natural language notes about the subject. Tokens are identified in the natural language notes. For each token, a corresponding intensity score is generated representing an intensity of m...

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Main Authors Doyen, Stephane Philippe, Nicholas, Peter James, Sughrue, Michael Edward
Format Patent
LanguageEnglish
Published 14.04.2022
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Abstract Electronic records are accessed from computer storage for a given subject, wherein the electronic records include natural language notes about the subject. Tokens are identified in the natural language notes. For each token, a corresponding intensity score is generated representing an intensity of match between the token and a particular dimension, wherein the intensity scores are each values on a first scale, wherein each dimension is one of a plurality of dimensions of a category out of a plurality of categories; generating rescaled-intensity scores from the intensity scores by rescaling the intensity scores from the first scale to a second scale different from the first scale. For each dimension of each category, a dimension-score is compiled based on the intensity scores; and categorizing the subject into at least one category based on the dimension scores. The subject is categorized into at least one category based on the dimension scores.
AbstractList Electronic records are accessed from computer storage for a given subject, wherein the electronic records include natural language notes about the subject. Tokens are identified in the natural language notes. For each token, a corresponding intensity score is generated representing an intensity of match between the token and a particular dimension, wherein the intensity scores are each values on a first scale, wherein each dimension is one of a plurality of dimensions of a category out of a plurality of categories; generating rescaled-intensity scores from the intensity scores by rescaling the intensity scores from the first scale to a second scale different from the first scale. For each dimension of each category, a dimension-score is compiled based on the intensity scores; and categorizing the subject into at least one category based on the dimension scores. The subject is categorized into at least one category based on the dimension scores.
Author Nicholas, Peter James
Doyen, Stephane Philippe
Sughrue, Michael Edward
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Snippet Electronic records are accessed from computer storage for a given subject, wherein the electronic records include natural language notes about the subject....
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SubjectTerms CALCULATING
COMPUTING
COUNTING
ELECTRIC DIGITAL DATA PROCESSING
HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATIONTECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING ORPROCESSING OF MEDICAL OR HEALTHCARE DATA
INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS
PHYSICS
Title NATURAL LANGUAGE PROCESSING OF ELECTRONIC RECORDS
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