Medical Named Entity Recognition (MedNER): Deep learning model for recognizing medical entities (drug, disease) from scientific texts

Miah, Md Saef Ullah and Junaida, Sulaiman and Talha, Sarwar and Islam, Saima Sharleen and Rahman, Mizanur and Haque, Md Samiul (2023) Medical Named Entity Recognition (MedNER): Deep learning model for recognizing medical entities (drug, disease) from scientific texts. In: EUROCON 2023 - 20th International Conference on Smart Technologies, Proceedings; 20th International Conference on Smart Technologies, EUROCON 2023 , 6-8 July 2023 , Torino. pp. 158-162.. ISBN 978-166546397-3

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Abstract

Medical Named Entity Recognition (MedNER) is an indispensable task in biomedical text mining. NER aims to recognize and categorize named entities in scientific literature, such as genes, proteins, diseases, and medications. This work is difficult due to the complexity of scientific language and the abundance of available material in the biomedical sector. Using domain-specific embedding and Bi-LSTM, we propose a novel NER model that employs deep learning approaches to improve the performance of NER on scientific publications. Our model gets 98% F1-score on a curated data-set of Covid-related scientific publications published in multiple web of science and pubmed indexed journals, significantly outperforming previous approaches deployed on the same data-set. Our findings illustrate the efficacy of our approach in reliably recognizing and classifying named entities (drug and disease) in scientific literature, opening the way for future developments in biomedical text mining.

Item Type:	Conference or Workshop Item (Paper)
Additional Information:	Indexed by Scopus
Uncontrolled Keywords:	Bi-LSTM; Deep learning in healthcare; Medical named entity recognition; Medical natural language processing; MedNER; Named entity recognition; NER; NLP
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software T Technology > T Technology (General) T Technology > TA Engineering (General). Civil engineering (General)
Faculty/Division:	Institute of Postgraduate Studies College of Engineering Faculty of Computing
Depositing User:	Mr Muhamad Firdaus Janih@Jaini
Date Deposited:	06 Nov 2023 04:28
Last Modified:	06 Nov 2023 04:28
URI:	http://umpir.ump.edu.my/id/eprint/38752
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