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documentation:cdm:note_nlp [2017/07/07 23:59]
rimma_belenkaya1
documentation:cdm:note_nlp [2017/07/08 00:00]
rimma_belenkaya1
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 |term_exists|No|Boolean|Term_exists is defined as a flag that indicates if the patient actually has or had the condition. Any of the following modifiers would make Term_exists false: Negation = true; Subject = [anything other than the patient]; Conditional = true; Rule_out = true; Uncertain = very low certainty or any lower certainties. A complete lack of modifiers would make Term_exists true. For the modifiers that are there, they would have to have these values: Negation = false; Subject = patient; Conditional = false; Rule_out = false; Uncertain = true or high or moderate or even low (could argue about low).| |term_exists|No|Boolean|Term_exists is defined as a flag that indicates if the patient actually has or had the condition. Any of the following modifiers would make Term_exists false: Negation = true; Subject = [anything other than the patient]; Conditional = true; Rule_out = true; Uncertain = very low certainty or any lower certainties. A complete lack of modifiers would make Term_exists true. For the modifiers that are there, they would have to have these values: Negation = false; Subject = patient; Conditional = false; Rule_out = false; Uncertain = true or high or moderate or even low (could argue about low).|
 |term_temporal|No|string(50)|Term_temporal is to indicate if a condition is “present” or just in the “past”. The following would be past: History = true; Concept_date = anything before the time of the report.| |term_temporal|No|string(50)|Term_temporal is to indicate if a condition is “present” or just in the “past”. The following would be past: History = true; Concept_date = anything before the time of the report.|
-|term_modifiers|No|string(2000)|Describes compactly all the modifiers extracted by nlp system. For example, “son has rash” → “negated=no,​subject=family,​certainty=undef,​conditional=false,​general=false”. Value will be saved as one of the modifiers|+|term_modifiers|No|string(2000)|Describes compactly all the modifiers extracted by nlp system. For example, “son has rash” → “negated=no,​subject=family,​certainty=undef,​conditional=false,​general=false”. Value will be saved as one of the modifiers.|
  
  
documentation/cdm/note_nlp.txt · Last modified: 2017/09/25 15:02 by clairblacketer