DRUG PREDICTION AND INTIMATION SYSTEM USING FUZZY BASED CONVOLUTIONAL NEURAL NETWORK
European Journal of Molecular & Clinical Medicine,
2020, Volume 7, Issue 6, Pages 2504-2523
AbstractIn present scenario, medical research centres have a prominent role in identifying new drugs due to the increasing ailments. There exists unique effect for each and every drug which might be either a good reaction or negative reaction. Hence there necessitates to obtain drugs impact which helps physician for prescribing replacement for the patients. The interpretations analysis stated by the drug users in online sites plays a major part in Drug reactions predictions. Modified Convolution Neural Network based Drug Prediction System (MCNN-DPS) is one of the methodology adopted earlier for the above predictions. There is no sharing of drug information in the earlier researches which might aid doctors for analysing besides replacement drugs recommendation. This research concentrates mainly on the above elucidated through an approach entitled Drug Prediction and Intimation System using Fuzzy based Convolutional Neural Network (DPIS-FCNN). The extraction of drug related posts is accomplished primarily from the online sites. Fuzzy based Convolutional Neural Network (FCNN) is greatly involved in drug reaction prediction. The logistic regression based clustering method is chiefly deployed for grouping those drugs beside with their reaction on the basis of their relevancy once prediction is done. The respective doctor receives this grouped information when they possess proper access permission. MATLAB simulation platform is greatly utilized for validating the entire research work and proved to attain improved outcome than the prevailing research works.
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