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In the present scenario, the accessibility of proper medical resources has reached a critical juncture, characterized by a scarcity of medical professionals and medical supplies in several geographical areas majorly in rural and semi-urban areas. Majority of uneducated and even educated people have opted to self-medication without proper professional guidance which can make their health conditions much worse. Capitalizing on the advancements in Machine Learning and its growing role in various domains, this study introduces an innovative drug recommendation system intended to reduce the burden on medical practitioners and help the society. The drug recommendation system works like an expert who can prescribe apt medicines. It assesses patients who have consumed specific drug and it uses mathematical and logical approaches to find out which drugs are more likely to work well based on given symptoms. The proposed system eradicates false suggestions by implying TF-IDF algorithm on the reviews to extract the essence of it.

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Enhanced Drug Recommendation Framework: Leveraging Sentiment Analysis in Drug Reviews Through Machine Learning Techniques

  • 会议论文

  • 发表日期：

    2025年

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  • B. Sindhu,
  • Shrija Madhu,
  • G. Taruni Chowdary,
  • D. Sai Venkata Abhiram,
  • K. G. S. Venkatesan

摘要

In the present scenario, the accessibility of proper medical resources has reached a critical juncture, characterized by a scarcity of medical professionals and medical supplies in several geographical areas majorly in rural and semi-urban areas. Majority of uneducated and even educated people have opted to self-medication without proper professional guidance which can make their health conditions much worse. Capitalizing on the advancements in Machine Learning and its growing role in various domains, this study introduces an innovative drug recommendation system intended to reduce the burden on medical practitioners and help the society. The drug recommendation system works like an expert who can prescribe apt medicines. It assesses patients who have consumed specific drug and it uses mathematical and logical approaches to find out which drugs are more likely to work well based on given symptoms. The proposed system eradicates false suggestions by implying TF-IDF algorithm on the reviews to extract the essence of it.