The Resource Temporal mining framework for risk reduction and early detection of chronic diseases, by Sowjanya Paladugu, (electronic resource)

Temporal mining framework for risk reduction and early detection of chronic diseases, by Sowjanya Paladugu, (electronic resource)

Label
Temporal mining framework for risk reduction and early detection of chronic diseases
Title
Temporal mining framework for risk reduction and early detection of chronic diseases
Statement of responsibility
by Sowjanya Paladugu
Creator
Contributor
Thesis advisor
Subject
Genre
Language
eng
Summary
Chronic diseases significantly affect the quality of life of over 25 million Americans and are among the most common health problems. Due to the complexity of these diseases, it is difficult for clinicians to analyze trends in patient data. Therefore, there is a need for informatics tools to efficiently monitor disease progression and to analyze trends in patient data to improve disease management. To this end, a temporal mining framework was developed to identify frequently occurring temporal patterns in patient measurements that may lead to development of diseases. The developed framework uses patient data collected over a series of regularly-scheduled clinical visits. Temporal sequences were preprocessed, discretized, and mined to identify frequent episodes in measurement sequences before the onset of a disease. Contrast mining was also performed to determine episodes significant to specific patient groups and to conduct side-by-side comparisons of episodes shared among patient groups. The efficacy of the temporal mining framework was evaluated via a case study of lymphedema. The framework was applied to a dataset to study the incidence and severity of lymphedema in post breast cancer patients. Temporal changes in limb volume (LV) measurement data were analyzed via the framework, with patients grouped based on body mass index, occurrence of post-operative swelling, and age. The analysis indicated that similar LV change episodes have varying probabilities of leading to lymphedema in various populations
Cataloging source
MUU
http://library.link/vocab/creatorDate
1984-
http://library.link/vocab/creatorName
Paladugu, Sowjanya
Degree
M. S.
Dissertation year
2010.
Granting institution
University of Missouri--Columbia
Illustrations
illustrations
Index
no index present
Literary form
non fiction
Nature of contents
  • dictionaries
  • bibliography
  • theses
http://library.link/vocab/relatedWorkOrContributorName
Shyu, Chi-Ren
http://library.link/vocab/subjectName
  • Association rule mining
  • Data mining
  • Lymphedema
  • Chronic diseases
  • Diagnosis
  • Medical records
Target audience
specialized
Label
Temporal mining framework for risk reduction and early detection of chronic diseases, by Sowjanya Paladugu, (electronic resource)
Instantiates
Publication
Note
  • Title from PDF of title page (University of Missouri--Columbia, viewed on November 3, 2010)
  • The entire thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file; a non-technical public abstract appears in the public.pdf file
  • Thesis advisor: Dr. Chi-Ren Shyu
Bibliography note
Includes bibliographical references
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Control code
733775694
Extent
1 online resource (ix, 64 pages)
Form of item
online
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Other physical details
illustrations (some color).
Specific material designation
remote
System control number
(OCoLC)733775694
Label
Temporal mining framework for risk reduction and early detection of chronic diseases, by Sowjanya Paladugu, (electronic resource)
Publication
Note
  • Title from PDF of title page (University of Missouri--Columbia, viewed on November 3, 2010)
  • The entire thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file; a non-technical public abstract appears in the public.pdf file
  • Thesis advisor: Dr. Chi-Ren Shyu
Bibliography note
Includes bibliographical references
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Control code
733775694
Extent
1 online resource (ix, 64 pages)
Form of item
online
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Other physical details
illustrations (some color).
Specific material designation
remote
System control number
(OCoLC)733775694

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