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You searched for subject:(Clinical datasets). Showing records 1 – 2 of 2 total matches.

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Anna University

1. Vijaya K. An intelligent predictive model for knowledge discovery from clinical datasets.

Degree: Information and Communication, 2011, Anna University

An Intelligent prediction model for the discovery of knowledge from clinical datasets is proposed and evaluated. The model has been specifically designed to be used by physicians as an aid for clinical decision making. The features supported by the model include extracting knowledge from the clinical datasets and representing the extracted knowledge in the form of rules or network parameters. The first component this research work focuses on techniques for extracting the knowledge from hepatitis data. This model has been tailored to include normalization, principal component analysis and fuzzy c-means clustering in the pre-mining subsystem. The second component extracted knowledge from time-series hepatitis data. The pre-mining subsystem processed the data to represent the variations of the data values with respect to the date of examination. The system extracted knowledge from hepatitis data using the techniques association rule mining algorithm, decision tree algorithm and neural network. The third component extracted knowledge from heart disease data. The pre-mining subsystem discretized the continuous valued attributes using entropy based discretization. The fourth component was also used to extract knowledge from heart disease data. The pre-mining subsystem was implemented to fuzzify the continuous valued attributes. A survey had been carried out on the studies carried out to identify correlation among cardiovascular, diabetes, hepatitis and anemia (renal). Some of the studies reveal that hepatitis is more prevalent among hemodialysis patients. Studies reveal that hepatitis is associated with diabetes; some of the studies identify positive correlation between them whereas others a negative correlation. Patient with hepatitis infection was found to have different cardiovascular risks when compared to a non infected patient. Studies show that diabetic patients are more prone to have cardiovascular risks.

References p. 101-111

Advisors/Committee Members: Khanna Nehemiah, H.

Subjects/Keywords: Intelligent predictive model; Clinical datasets; Fuzzy c-mean clustering; Cardiovascular

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

K, V. (2011). An intelligent predictive model for knowledge discovery from clinical datasets. (Thesis). Anna University. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/13971

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

K, Vijaya. “An intelligent predictive model for knowledge discovery from clinical datasets.” 2011. Thesis, Anna University. Accessed January 17, 2020. http://shodhganga.inflibnet.ac.in/handle/10603/13971.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

K, Vijaya. “An intelligent predictive model for knowledge discovery from clinical datasets.” 2011. Web. 17 Jan 2020.

Vancouver:

K V. An intelligent predictive model for knowledge discovery from clinical datasets. [Internet] [Thesis]. Anna University; 2011. [cited 2020 Jan 17]. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/13971.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

K V. An intelligent predictive model for knowledge discovery from clinical datasets. [Thesis]. Anna University; 2011. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/13971

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of New Mexico

2. Morrison, Molly Aileen. Social Determinants of Health and Variability in Weight Trends of Children of Low Income Families Living in New Mexico.

Degree: Individual, Family, and Community Education, 2019, University of New Mexico

When evaluating the prevalence of obesity rates throughout New Mexico (NM), it appears these rates have reached a plateau. A recent study conducted by the NM Department of Health (DOH) found that NM was among 19 other states that have had a first time decrease in child obesity rates among low income families. However, when examined deeper, when looking at geographical areas throughout NM, hidden geography of weight disparities become apparent. Although obesity rates may have decreased in some areas, they have increased in others. The purpose of this study is to effectively evaluate variability in weight trends between geographical areas throughout NM and to evaluate the relationship between obesity rates and specific socioeconomic determinants. This study utilized two mapped datasets, created at two distinct times, that were conjoined to form a trend map as well as a swipe map that allows for visual exploration of child weight trends from 2013 to 2015. Pearson correlation evaluated the relationship between socioeconomic variables and obesity rates. Statistical significance of changes in obesity rates in geographical areas was determined using two standard deviations above and below each estimate to obtain a 95% confidence interval for the coefficient estimate. A significant relationship was found between one socioeconomic variable (proportion of grandchildren living with grandparents without parent present) and a significant increase in obesity rates was seen in over 10 geographical areas throughout NM. All WIC management, early childhood groups, obesity prevention groups and researchers can utilize suggested findings of this study to effectively focus healthcare in areas where obesity rates have increased and improve quality of care in these communities. Results of this study can provide a pathway for the improvement of WIC program management and development, social conditions/environments and continuity of care. Advisors/Committee Members: Deborah Cohen, DCN, RDN, Thomas N Scharmen, MA, MPH, Diana-Gonzales-Pacheco, DCN, RDN.

Subjects/Keywords: Nutrition; public health; child obesity; mapped datasets; Dietetics and Clinical Nutrition; Education; Epidemiology; Public Health Education and Promotion

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Morrison, M. A. (2019). Social Determinants of Health and Variability in Weight Trends of Children of Low Income Families Living in New Mexico. (Masters Thesis). University of New Mexico. Retrieved from https://digitalrepository.unm.edu/educ_ifce_etds/77

Chicago Manual of Style (16th Edition):

Morrison, Molly Aileen. “Social Determinants of Health and Variability in Weight Trends of Children of Low Income Families Living in New Mexico.” 2019. Masters Thesis, University of New Mexico. Accessed January 17, 2020. https://digitalrepository.unm.edu/educ_ifce_etds/77.

MLA Handbook (7th Edition):

Morrison, Molly Aileen. “Social Determinants of Health and Variability in Weight Trends of Children of Low Income Families Living in New Mexico.” 2019. Web. 17 Jan 2020.

Vancouver:

Morrison MA. Social Determinants of Health and Variability in Weight Trends of Children of Low Income Families Living in New Mexico. [Internet] [Masters thesis]. University of New Mexico; 2019. [cited 2020 Jan 17]. Available from: https://digitalrepository.unm.edu/educ_ifce_etds/77.

Council of Science Editors:

Morrison MA. Social Determinants of Health and Variability in Weight Trends of Children of Low Income Families Living in New Mexico. [Masters Thesis]. University of New Mexico; 2019. Available from: https://digitalrepository.unm.edu/educ_ifce_etds/77

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