Enhanced pre-trained general natural language model for Bio-medical domain

Registration ID: IJNRD_217420

Published ID: IJNRD2404088

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Sikkireddy Lakshmi Shanmukha, Sruthi Siralu , Sathvika Sasanapuri , Rahul Sandy Devarapalli

Bio-Medical, BERT

In recent years, the field of Natural Language Processing (NLP) has witnessed the remarkable advancements with emergence of general language models like BERT, GPT-3. These models have demonstrated impressive capabilities in understanding and generating human like text across wide range of domains. However, their potential remains largely untapped when it comes to specialized domains such as biomedicine. This proposed work aims to explore and harness the latent potential of general language models within the biomedical domain. The biomedical field is characterized by its intricate terminology, complex relationships, and vast volumes of specialized textual data, ranging from clinical notes and research articles to medical records and drug databases. This proposed work endeavours to bridge the gap between the capabilities of existing language models and the unique requirements of the biomedical domain. The primary objective of this proposed work is to develop a tailored pre-training approach that optimizes language models for biomedical tasks. By delving into domain-specific data sources and curating a comprehensive biomedical language corpus, this work intend to enhance the language model's understanding of biomedical concepts, relationships, and context. Additionally, this work seeks to design fine-tuning strategies that adapt the pre-trained models to perform specific biomedical tasks, such as text classification, relation extraction, and medical text summarization. This paper overcomes this difficulties of previous papers of bio-medical domain in language understanding by gaining a good performance.

Published Paper   E-Certificate

Sikkireddy Lakshmi Shanmukha, Sruthi Siralu , Sathvika Sasanapuri , & Rahul Sandy Devarapalli (April-2024). Enhanced pre-trained general natural language model for Bio-medical domain. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(4), a718-a729. https://ijnrd.org/papers/IJNRD2404088.pdf

Volume 9 Issue 4, April-2024

Pages : a718-a729

Paper Reg. ID: IJNRD_217420

Published Paper Id: IJNRD2404088

Downloads: 000121992

Research Area: Computer Science & Technology 

Author Type: Indian Author

Country: Kakinada District, Andhra Pradesh, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2404088.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2404088

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

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