Biomedical Research
Biomedical research is increasingly leveraging artificial intelligence, particularly large language models (LLMs), to accelerate discovery and improve healthcare. Current research focuses on adapting LLMs for various biomedical tasks, including hypothesis generation, clinical trial analysis, and medical image interpretation, often integrating them with knowledge graphs and employing techniques like retrieval-augmented generation and multimodal learning. This work aims to improve the efficiency and accuracy of biomedical research while addressing challenges related to data privacy, bias, and model explainability, ultimately impacting diagnostics, drug discovery, and personalized medicine.
Papers
An LLM-based Knowledge Synthesis and Scientific Reasoning Framework for Biomedical Discovery
Oskar Wysocki, Magdalena Wysocka, Danilo Carvalho, Alex Teodor Bogatu, Danilo Miranda Gusicuma, Maxime Delmas, Harriet Unsworth, Andre Freitas
A Refer-and-Ground Multimodal Large Language Model for Biomedicine
Xiaoshuang Huang, Haifeng Huang, Lingdong Shen, Yehui Yang, Fangxin Shang, Junwei Liu, Jia Liu