Deep Learning Approach to Compose Short Stories Based on Online Hospital Reviews of Tirunelveli Region

Deep learning methods have received increasing attention in recent years from a variety of businesses, including healthcare, for the analysis and extraction of insightful data from Internet reviews. In this study, we tried to generate short stories via hospital reviews (SSHR) using a combination of deep learning methods, the convolutional variational autoencoder (CVAE) with the Bahdanau attention mechanism. This model was trained using a manually collected dataset of Tirunelveli Hospital online reviews, and the generated stories were not sequential due to the low training data; this model can be improved using a huge dataset, it is quite possible to capture the key information from online reviews. The CVAE method was used to learn the underlying distribution of the reviews, while the Bahdanau attention mechanism was employed to improve the clarity and flow of the generated text. The experimental outcomes demonstrate that this approach can effectively generate short stories. If it is trained with large amounts of data, the stories will be coherent and informative, providing valuable insights for healthcare professionals and patients.