Publication Type : Conference Paper
Publisher : Advances in Computational Intelligence and Communication Technology, Springer Singapore
Source : Advances in Computational Intelligence and Communication Technology, Springer Singapore, Singapore (2021)
Url : https://link.springer.com/chapter/10.1007/978-981-15-1275-9_27
ISBN : 9789811512759
Campus : Bengaluru
School : Department of Computer Science and Engineering, School of Engineering
Department : Computer Science
Year : 2021
Abstract : The discharge summary contains voluminous information regarding the patient like history, symptoms, investigations, treatment, medication, etc. Though the discharge summary has a general structured way of representation, it is still not structured in a way that clinical systems can process. Different natural language processing (NLP) and machine learning techniques have been explored on the discharge summaries to extract various interesting information. Text mining techniques have been carried out in public and private discharge summaries. This survey discusses different tasks performed on discharge summaries and the existing tools which have been explored. The major dataset which has been used in existing research is also discussed. A common outline of system architectures on discharge summaries across various researches is explored. Major challenges in extracting information from discharge summaries are also detailed.
Cite this Research Publication : Priyanka Vivek, Gupta, D., and Devi, B. Indira, “A Survey of Text Mining Approaches, Techniques, and Tools on Discharge Summaries”, in Advances in Computational Intelligence and Communication Technology, Singapore, 2021.