MedNLP: Medical Domain-Specific Text Summarization and Named Entity Recognition using BERT and GPT Models
Year: 2025
Type: article
Abstract: This project leverages advanced NLP techniques, specifically BERT and GPT-2, to address challenges in the medical domain by focusing on Named Entity Recognition (NER) and Text Summarization.It aims to accurately identify and classify medical entities, such as diseases and medications, and generate concise summaries from clinical notes and medical literature.The approach involves fine-tuning BERT for precise recognition of complex medical terms and utilizing GPT-2 to produce coherent summaries.By collecting domainspecific datasets, performing data preprocessing, and refining the models, the project enhances the accessibility of medical information, thereby contributing to improved patient care and medical research through more efficient data extraction and summarization.
Authors: B Jyothi, Khaja Mastan B, Durga Sailaja Meruga, Jashwanth N
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: bronze
OpenAlex ID: W4409865670