Automatic Text Summarization for Medical Dataset-An Analysis

This review paper explores the application of deep learning techniques in abstractive text summarization, with a focus on their relevance to medical datasets. Abstractive text summarization is a crucial area of natural language processing, with the potential to significantly impact the field of healthcare and medical research. The paper provides a concise and crisp examination of the various deep learning models, methods, and algorithms employed in generating abstractive summaries from medical texts. It also highlights the challenges, trends, and potential future directions in this domain. The primary objective of this review is to offer insights into the current state-of-the-art methods for abstractive text summarization in the medical domain and their implications for healthcare professionals, researchers, and data scientists.