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All Journal Indonesian Journal of Multidisciplinary Science
Begum, S. Gousiya
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Humanities Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Public Health Social Sciences

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Drug Recommendations Using a “Reviews and Sentiment Analysis” by a Recurrent Neural Network Begum, S. Gousiya; Sree, P. Kiran
Indonesian Journal of Multidisciplinary Science Vol. 2 No. 9 (2023): Indonesian Journal of Multidisciplinary Science
Publisher : International Journal Labs

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55324/ijoms.v2i9.530

Abstract

Drug Recommendation systems have the capability to recommend drugs. On daily basis, a huge amount of data is being generated by the patients. All the valuable data can be properly utilized for creating a reliable drug recommendation system. In this paper, the researchers aimed to propose a system for drug recommendations. The main scope of the system is to predict the correct medication based on reviews and ratings. The proposed system uses Natural Language Processing techniques (NLP) and Recurrent Neural Network (RNN). The researchers also considered various metrices such as precision, recall, accuracy, f1 Score, roc curve as the measures of the system performance. Natural Language Processing techniques were used for gathering useful information from patients data, and RNN is a machine learning methodology, that works really well when it comes to analysing textual data. The system considers various patient data attributes like age, gender, dosage, medical history, symptom in order to make appropriate predictions. As the result, the proposed system has the potential to help medical professionals in making informed drug recommendations.
Co-Authors Sree, P. Kiran