Review paper of drug recommendation system

Srinath R; Arpitha Vasudev; Krishnaveni Navalgund; Kiran R S

Review paper of drug recommendation system

Authors: Srinath R, Arpitha Vasudev, Krishnaveni Navalgund, Kiran R S

Unique Paper ID: 162593
Volume: 10
Issue: 10
PageNo: 458-462

Keywords: No Keywords Found

Abstract:
This study offers a brand-new approach to medication recommendation that is based on user-generated review sentiment analysis. By analysing the sentiment expressed in these evaluations, our method leverages machine learning techniques to increase the accuracy of medication recommendations. We use algorithms for sentiment categorization and natural language processing to interpret user sentiments in order to offer a more nuanced understanding of medication experiences. As part of our process, we gather a wide range of drug reviews and use a strong sentiment analysis model. The system's ability to incorporate aspects like sentiment polarity, user feedback, and contextual data allows it to pick up on minute details in user encounters. By utilising machine learning algorithms, our system becomes capable of learning and adjusting to changing drug review patterns, which guarantees its efficacy in constantly changing healthcare environments .This is suggested system for medicine recommendation.

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ISSN: 2349-6002
Volume: 10
Issue: 10
PageNo: 458-462

Review paper of drug recommendation system

Available:https://ijirt.org/Article?manuscript=162593

Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

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