Ranging from primary health care institutions to
the big health care centers, every healthcare organization
uses an information system which stores, processes and
retrieves healthcare data. Healthcare data stored
electronically are used to improve healthcare planning.
Healthcare centers and academic centers also use these data
for education and research. Data Mining is the process of
finding correlations or patterns among dozens of fields in
large relational databases storing large set of transactional
data. It basically has four modules: Classification, the
grouping of data in predefined classes; , clustering, the
association of data in classes; Regression, which models the
data of the minimum error and Association, which find
relationship among data objects.This research paper presents
our findings on the strategic management of health care
system for effective health care planning and advancement it
has brought to the health care sector.
O. I. Omotoso : Department of Computer Science and Engineering, LadokeAkintola University of
Technology, Ogbomoso, Oyo State.
I. A. Adeyanju : Department of Computer Science and Engineering, LadokeAkintola University of
Technology, Ogbomoso, Oyo State.
S. A. Ibraheem : Department of Computer Science and Engineering, LadokeAkintola University of
Technology, Ogbomoso, Oyo State.
K. S. Ibrahim : Department of Computer Science and Engineering, LadokeAkintola University of
Technology, Ogbomoso, Oyo State.
SMS-EHCP
strategic
Management
Health
Care
Planning
Data and Mining
For each characteristic, analysis of how the results vary
whenever test mode is changed was noticed. Measure of
interest includes the analysis of classifiers on the datasets,
the results are described in value of prediction made by
Zero R classification algorithm(for dataset with nominal
class value), correlation coefficient (for dataset with numeric class value), mean absolute error, root mean
squared error, relative absolute error, root relative squared
error after applying the Training set test, Supplied test set,
Cross-Validation, and Percentage split methods. A datasets
(Medical Record) have nominal class value. All the testing
methods predicted Plamodiasis for ailment and Rainy
season was predicted as matching season for the predicted
ailment.
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