An Artificial Intelligent-Based Chatbot for Dosage Prediction of Medicine Using Noval Deep Reinforcement Learning with Natural Language Processing

The aim is to create an artificial conversation entity (chatbot) using Python to predict dosage of medicine for healthcare treatments. Materials and Methods: Two algorithms, deep reinforcement algorithms, are compared with deep learning algorithm sample size taken 28. G power of 80% and sample size...

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Bibliographic Details
Published inECS transactions Vol. 107; no. 1; pp. 14841 - 14853
Main Authors B, Phani Raghava, Ashok Kumar, S.
Format Journal Article
LanguageEnglish
Published The Electrochemical Society, Inc 24.04.2022
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ISSN1938-5862
1938-6737
DOI10.1149/10701.14841ecst

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Summary:The aim is to create an artificial conversation entity (chatbot) using Python to predict dosage of medicine for healthcare treatments. Materials and Methods: Two algorithms, deep reinforcement algorithms, are compared with deep learning algorithm sample size taken 28. G power of 80% and sample size is calculated using G power tool. Results and Discussion: Performances of the score model validated test set accuracy with 95% confidence interval for deep reinforcement algorithm with different sub-samples having different number of intents comparing with deep learning, which has 85% accuracy. Conclusion: From the results, it is concluded that proposed algorithm deep reinforcement will produce better results than the existing algorithm.
ISSN:1938-5862
1938-6737
DOI:10.1149/10701.14841ecst