Analysis of the feelings in the reviews of patients versus the evaluation of the ease of use, effectiveness, and satisfaction of prescribed medications
DOI:
https://doi.org/10.70099/BJ/2024.01.01.24Keywords:
Natural language processing, sentiment analysis, BERT, medication satisfactionAbstract
The sentimental polarity of patients' medical treatments is decisive for therapeutic adherence, especially in managing chronic diseases. Patients value the effects of medications differently, while health personnel do it from a practical perspective. For this, patient reviews have been taken in unstructured text to the diversity of drugs available on the WebMD site. A numerical assessment accompanies these data on a Likert scale of the variables for "EaseofUse", "Effectiveness," and "Satisfaction". Using an NLP model called RoBERTa; the opinions have been analyzed, finding that neutral opinions are maintained against positive scales of "EaseofUse" and "Effectiveness," but negative opinions regarding "Satisfaction," where the evaluations are divided into the extremes. The analysis has been done statistically using frequencies and diagrams of pairs between feelings and variables of interest.
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