Peng, Xueqing

Improving large language models for clinical named entity recognition via prompt engineering

Hu, Y., Chen, Q., Du, J., Peng, X., Keloth, V. K., Zuo, X., Zhou, Y., Li, Z., Jiang, X., Lu, Z., et al. (2024) · Journal of the American Medical Informatics Association

Topic ModelingBiomedical Text Mining and Ontologies

Cited by 314

Benchmarking large language models for biomedical natural language processing applications and recommendations

Chen, Q., Hu, Y., Peng, X., Xie, Q., Jin, Q., Gilson, A., Singer, M. B., Ai, X., Lai, P.-T., Wang, Z., et al. (2025) · Nature Communications

Biomedical Text Mining and OntologiesTopic Modeling

Cited by 219

Advancing entity recognition in biomedicine via instruction tuning of large language models

Keloth, V. K., Hu, Y., Xie, Q., Peng, X., Wang, Y., Zheng, A., Selek, M., Raja, K., Wei, C. H., Jin, Q., et al. (2024) · Bioinformatics

Biomedical Text Mining and OntologiesTopic Modeling

Cited by 104

Medical foundation large language models for comprehensive text analysis and beyond

Xie, Q., Chen, Q., Chen, A., Peng, C., Hu, Y., Lin, F., Peng, X., Huang, J., Zhang, J., Keloth, V., et al. (2025) · npj Digital Medicine

Artificial Intelligence in Healthcare and EducationTopic Modeling

Cited by 74

Me LLaMA: Foundation Large Language Models for Medical Applications

Xie, Q., Chen, Q., Chen, A., Peng, C., Hu, Y., Lin, F., Peng, X., Huang, J., Zhang, J., Keloth, V., et al. (2024) · arXiv

Artificial Intelligence in Healthcare and EducationTopic Modeling

Cited by 8