Drug Review: Sentiment Analysis, Using Advanced Machine Learning

"Sentiment Analysis of Drug Reviews Using Machine Learning Techniques," focuses on employing advanced machine learning methods, including Bidirectional LSTM and TF-IDF, to analyze sentiments expressed in clinical drug reviews. The aim is to develop sentiment analysis model capable of classifying and describing the patient experiences with medications. the usage of Bidirectional LSTM architecture to capture contextual dependencies within sequential data, enhancing the accuracy of sentiment predictions is used. Additionally, the TF-IDF technique is employed for feature extraction, emphasizing the importance of sentiments of patients and addressing some challenges due to language. The performance results obtained during evaluation of the model contains an accuracy of 94.21%. Thus, the usage of these techniques aims to provide a comprehensive understanding of sentiment patterns in clinical drug reviews, offering valuable insights for healthcare professionals.