Drug recommendation using recurrent neural networksaugmented with cellular automata

Abstract

Drug recommendation systems are systems that have the capability to recommend drugs. On a daily basis, a hugeamount of data is being generated by the patients. All this valuable data can be properly utilized to create a reliabledrug recommendation system. In this paper, we recommend a system for drug recommendations. The main scopeof our system is to predict the correct medication based on reviews and ratings. Our proposed system uses naturallanguage processing techniques (NLP), recurrent neural networks (RNN), and cellular automata (CA). We alsoconsidered various metrics like precision, recall, accuracy, F1 score, and ROC curve as measures of our system’sperformance. NLP techniques are being used for gathering useful information from patient data, and RNN is amachine learning methodology that works really well in analyzing textual data. The system considers various patientdata attributes like age, gender, dosage, medical history, and symptoms in order to make appropriate predictions.The proposed system has the potential to help medical professionals make informed drug recommendations.