Harnessing NLP for enhanced extraction of functional neurological disorder (FND) terminologies from clinical reports

Mashuk, Md Shadab; Kamilla, K; Yang, L; Daniela, D; Ashley, W; Shumit, S; Rajiv, M; Lana, Y; Matthew, S

Abstract

Functional Neurological Disorder (FND) is a complex condition that presents significant diagnostic and management challenges for healthcare professionals. This study investigates the variability in FND terminology used across different professional groups. We analyzed a sample of clinical letters from Salford Royal, using Natural Language Processing (NLP) to extract and categorize the terms used to describe FND. Our findings highlight notable inconsistencies in the current clinical vocabularies used for FND, underlining the need for standardization of terminology. This standardization can enhance inter-professional communication, streamline clinical decision making, and ultimately lead to improved patient care. Our study lays the groundwork for future research aimed at developing a universally adopted, standardized clinical vocabulary for FND.

Citation

Mashuk, M. S., Kamilla, K., Yang, L., Daniela, D., Ashley, W., Shumit, S., …Matthew, S. (2023, June). Harnessing NLP for enhanced extraction of functional neurological disorder (FND) terminologies from clinical reports. Poster presented at IDSAI Advances in Data Science and AI Conference 2023, University of Manchester

• Presentation Conference Type: Poster
• Conference Name: IDSAI Advances in Data Science and AI Conference 2023
• Conference Location: University of Manchester
• Start Date: Jun 13, 2023
• End Date: Jun 13, 2023
• Deposit Date: May 6, 2024
• Related Public URLs: https://www.idsai.manchester.ac.uk/connect/events/conference/advances-in-data-science-and-ai-conference-2023/