Publication Type : Conference Paper
Publisher : 2019 9th International Conference on Advances in Computing and Communication (ICACC), IEEE
Source : 2019 9th International Conference on Advances in Computing and Communication (ICACC), IEEE, Kochi, India (2019)
Url : https://ieeexplore.ieee.org/document/8986171
Campus : Bengaluru
School : Department of Computer Science and Engineering, School of Engineering
Department : Computer Science
Year : 2019
Abstract : Pituitary Adenoma, a brain tumour that resembles other diseases, poses a diagnostic challenge for primary-care doctors. This first of its kind study utilizes the hospital discharge summaries obtained from the National Institute of Mental Health and Neuroscience (NIMHANS), Bangalore, India to address this issue. Patient discharge summaries are rich in information pertaining to the disease, the history of diagnoses and eventual treatment. Using regular expression and Natural Language Processing rules, we automatically extracted clinical concepts from the NIMHANS data. This was done post Metamap parsing of the discharge summaries and annotating it using “BIO” tagging. The concept-value pairs were represented in the form of an Analytical Base Table which will help develop a decision support system that can enable early diagnosis of this type of brain tumour.
Cite this Research Publication : Priyanka Vivek, Gupta, D., Devi, B. Indira, and Bhat, N. Raghav, “Automated Clinical Concept-Value Pair Extraction from Discharge Summary of Pituitary Adenoma Patients”, in 2019 9th International Conference on Advances in Computing and Communication (ICACC), Kochi, India, 2019.
