Document Detail


Natural language processing of spoken diet records (SDRs).
MedLine Citation:
PMID:  17238382     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Dietary assessment is a fundamental aspect of nutritional evaluation that is essential for management of obesity as well as for assessing dietary impact on chronic diseases. Various methods have been used for dietary assessment including written records, 24-hour recalls, and food frequency questionnaires. The use of mobile phones to provide real-time dietary records provides potential advantages for accessibility, ease of use and automated documentation. However, understanding even a perfect transcript of spoken dietary records (SDRs) is challenging for people. This work presents a first step towards automatic analysis of SDRs. Our approach consists of four steps - identification of food items, identification of food quantifiers, classification of food quantifiers and temporal annotation. Our method enables automatic extraction of dietary information from SDRs, which in turn allows automated mapping to a Diet History Questionnaire dietary database. Our model has an accuracy of 90%. This work demonstrates the feasibility of automatically processing SDRs.
Authors:
Ronilda Lacson; William Long
Publication Detail:
Type:  Evaluation Studies; Journal Article    
Journal Detail:
Title:  AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium     Volume:  -     ISSN:  1942-597X     ISO Abbreviation:  AMIA Annu Symp Proc     Publication Date:  2006  
Date Detail:
Created Date:  2007-01-22     Completed Date:  2007-09-28     Revised Date:  2013-06-06    
Medline Journal Info:
Nlm Unique ID:  101209213     Medline TA:  AMIA Annu Symp Proc     Country:  United States    
Other Details:
Languages:  eng     Pagination:  454-8     Citation Subset:  IM    
Affiliation:
Massachusetts Institute of Technology (MIT), Cambridge, MA, USA.
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MeSH Terms
Descriptor/Qualifier:
Algorithms*
Automatic Data Processing
Diet Records*
Humans
Natural Language Processing*
Questionnaires
Speech
Comments/Corrections

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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