Optimized Biomedical Question-Answering Services with LLM and Multi-BERT Integration
- Publisher:
- IEEE
- Publication Type:
- Conference Proceeding
- Citation:
- 2024 IEEE International Conference on Data Mining Workshops (ICDMW), 2025, 00, pp. 164-173
- Issue Date:
- 2025-03-18
Open Access
Copyright Clearance Process
- Recently Added
- In Progress
- Open Access
This item is open access.
We present a refined approach to biomedical question answering QA services by integrating large language models LLMs with Multi BERT configurations By enhancing the ability to process and prioritize vast amounts of complex biomedical data this system aims to support healthcare professionals in delivering better patient outcomes and informed decision making Through innovative use of BERT and BioBERT models combined with a multi layer perceptron MLP layer we enable more specialized and efficient responses to the growing demands of the healthcare sector Our approach not only addresses the challenge of overfitting by freezing one BERT model while training another but also improves the overall adaptability of QA services The use of extensive datasets such as BioASQ and BioMRC demonstrates the system s ability to synthesize critical information This work highlights how advanced language models can make a tangible difference in healthcare providing reliable and responsive tools for professionals to manage complex information ultimately serving the broader goal of social good through improved care and data driven insights
Please use this identifier to cite or link to this item: