Authors:Â Yadav Dhanashri M., Yadav Gauri B., Zargad Vrushali S., Shinde Varsha N.
Abstract:Â Many peoples are caring about the health and medical diagnosis problems. However,according to the admin-istrations report, more than 200 thousand people in China and 100 thousand in USA, die each year due to medication errors. More than 42 % medication errors are caused by doctors because experts write the prescription according to their experiences which are quite limited. Many Data mining and recommender technologies provide possible knowledge from diagnosis history details and help doctors to provide suggestion medication correctly to reduce medication error successfully. We suggest and implement a medicine recommender system that applies data mining technologies to the recommendation system. We study the medicine recommendation algorithms of the SVM (Support Vector Machine),BP neural network,ID3 decision tree algorithms based on diagnosis data. For better performance SVM recommendation model is selected. We also recommend a mistake-check method to ensure the diagnosis correctness and service quality. Our system can give medication recommendation with an excellent efficiency, accuracy and scalability.
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