A Hybrid Approach for Extractive Summarization of Medical Documents

Text summarization helps us to obtain the most significant content from any document saving time and resources. Many researches of automatic summarization have been done with documents of general domain. In recent years, artificial intelligence and machine learning are being more and more integrated with medical field. As the field of medical requires efficiency more than any other field of science, proper summarization of medical documents is important. Some works and studies have been done in this topic but they have many limitations and restrictions. In this paper, we have presented a hybrid approach for extractive summarization of medical documents. In the combinational method, we have filtered neutral content of a document through sentiment analysis and with interconnection and content of sentences and presence of keyphrases, summarization has been done. After evaluation, the introduced method has shown promise with good scores.