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On robust methodologies for managing public health care systems.

Nimmagadda SL, Dreher HV - Int J Environ Res Public Health (2014)

Bottom Line: In addition to rigor on data mining and visualization, an added focus is on values of interpretation of data views, from processed full-bodied diagnosis, subsequent prescription and appropriate medications.The proposed methodology, is a robust back-end application, for web-based patient-doctor consultations and e-Health care management systems through which, billions of dollars spent on medical services, can be saved, in addition to improving quality of life and average life span of a person.Government health departments and agencies, private and government medical practitioners including social welfare organizations are typical users of these systems.

View Article: PubMed Central - PubMed

Affiliation: School of Information Systems, CBS, Curtin University, Perth, 6102 WA, Australia. shastri.nimmagadda2011@gmail.com.

ABSTRACT
Authors focus on ontology-based multidimensional data warehousing and mining methodologies, addressing various issues on organizing, reporting and documenting diabetic cases and their associated ailments, including causalities. Map and other diagnostic data views, depicting similarity and comparison of attributes, extracted from warehouses, are used for understanding the ailments, based on gender, age, geography, food-habits and other hereditary event attributes. In addition to rigor on data mining and visualization, an added focus is on values of interpretation of data views, from processed full-bodied diagnosis, subsequent prescription and appropriate medications. The proposed methodology, is a robust back-end application, for web-based patient-doctor consultations and e-Health care management systems through which, billions of dollars spent on medical services, can be saved, in addition to improving quality of life and average life span of a person. Government health departments and agencies, private and government medical practitioners including social welfare organizations are typical users of these systems.

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Related in: MedlinePlus

Multidimensional model of different qualities of foods that affect the blood sugar levels.
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ijerph-11-01106-f007: Multidimensional model of different qualities of foods that affect the blood sugar levels.

Mentions: For example, though for sure the trend is changing, most American families do not prefer whole grains and vegetables on their shopping list. Europeans and Mediterranean people are vigilant on their diets, and especially prefer appetizing dishes made from vegetables, fruits and whole grains. Africans regularly consume medium to moderate fat meals with lot of vegetables, green bananas (steamed) and with lots of red meat including fish, fresh fruits and nuts. African populations, though cautious on sugar intake, are affected by high blood sugar levels. Asians, especially Indians include white sugar intake in their regular meals. Unlike Indians, intake of sugar by Chinese and Japanese is moderately low, especially among the aged population. Most of the sugar-related diseases are among Asian populations. As documented and interpreted in [13], there are 177 classes (dimensions), 53 properties (attributes) and 632 data instances, in food domain ontologies compatible for domain integration criteria. Countrywise data instances acquired worldwide, are populated within dimension and fact-data tables. As per schema design and business constraints narrated in Figure 7, instances from multiple dimensions and fact tables are mapped.


On robust methodologies for managing public health care systems.

Nimmagadda SL, Dreher HV - Int J Environ Res Public Health (2014)

Multidimensional model of different qualities of foods that affect the blood sugar levels.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3924495&req=5

ijerph-11-01106-f007: Multidimensional model of different qualities of foods that affect the blood sugar levels.
Mentions: For example, though for sure the trend is changing, most American families do not prefer whole grains and vegetables on their shopping list. Europeans and Mediterranean people are vigilant on their diets, and especially prefer appetizing dishes made from vegetables, fruits and whole grains. Africans regularly consume medium to moderate fat meals with lot of vegetables, green bananas (steamed) and with lots of red meat including fish, fresh fruits and nuts. African populations, though cautious on sugar intake, are affected by high blood sugar levels. Asians, especially Indians include white sugar intake in their regular meals. Unlike Indians, intake of sugar by Chinese and Japanese is moderately low, especially among the aged population. Most of the sugar-related diseases are among Asian populations. As documented and interpreted in [13], there are 177 classes (dimensions), 53 properties (attributes) and 632 data instances, in food domain ontologies compatible for domain integration criteria. Countrywise data instances acquired worldwide, are populated within dimension and fact-data tables. As per schema design and business constraints narrated in Figure 7, instances from multiple dimensions and fact tables are mapped.

Bottom Line: In addition to rigor on data mining and visualization, an added focus is on values of interpretation of data views, from processed full-bodied diagnosis, subsequent prescription and appropriate medications.The proposed methodology, is a robust back-end application, for web-based patient-doctor consultations and e-Health care management systems through which, billions of dollars spent on medical services, can be saved, in addition to improving quality of life and average life span of a person.Government health departments and agencies, private and government medical practitioners including social welfare organizations are typical users of these systems.

View Article: PubMed Central - PubMed

Affiliation: School of Information Systems, CBS, Curtin University, Perth, 6102 WA, Australia. shastri.nimmagadda2011@gmail.com.

ABSTRACT
Authors focus on ontology-based multidimensional data warehousing and mining methodologies, addressing various issues on organizing, reporting and documenting diabetic cases and their associated ailments, including causalities. Map and other diagnostic data views, depicting similarity and comparison of attributes, extracted from warehouses, are used for understanding the ailments, based on gender, age, geography, food-habits and other hereditary event attributes. In addition to rigor on data mining and visualization, an added focus is on values of interpretation of data views, from processed full-bodied diagnosis, subsequent prescription and appropriate medications. The proposed methodology, is a robust back-end application, for web-based patient-doctor consultations and e-Health care management systems through which, billions of dollars spent on medical services, can be saved, in addition to improving quality of life and average life span of a person. Government health departments and agencies, private and government medical practitioners including social welfare organizations are typical users of these systems.

Show MeSH
Related in: MedlinePlus