ENDORSEMENT OF SMALL PATIENTS POPULATION STUDY THROUGH DATA MINING CLASSIFICATION: SIGNIFICANCE TO MANIFEST DRUG INTERACTION STUDY OF CARDIOVASCULAR DOSAGE FORMULATION
Journal Title: International Journal of Pharmacy and Pharmaceutical Sciences - Year 2014, Vol 6, Issue 8
Abstract
Objective: A simple, sensitive, precise computational classifiers justifies the positive indication of drug interaction through statistical validation and confirms for further root level investigation.Methods: The blood pressure (BP) & Lipid profile valued data sheet was prepared from 100 patients those were chronically treating with cardiovascular formulation consisting Atorvastatin 10mg + Olmesartan 20mg. The data sheet contains 100 patients with 10 variables and final decision attributes of working & non-working. Then, with the operation of seven different related classifier the details of % of accuracy by class, correct & incorrect classified instance and stratified cross- validation were estimated. Those statistical results of classifiers were compared, correlate and interpreted to bring a fixed conclusion based on it.Results: The % of accuracy for all classifiers results commonly 95.9596 %, 93.9394 % and 96.9697 % and inter-depending class attributes denoting by a = NW & b =W Matrix values are 84│11, 84│9, 87│9 respectively. Thus, the accuracy is excellent covering within the limits of (±15%) as a correct classified instant.Conclusion: Statistical computation on less populated patients through classifiers, evidentially confirms the drug-interaction profile of collected data through data mining process. So that, it can proceeds further upto root level through instrumental bioanalysis.Â
Authors and Affiliations
Rakesh Das, Subhasis Dan, Tapan Kumar Pal
Keywords
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