Liu, Zhengliang

Summary of ChatGPT-Related Research and Perspective Towards the Future of Large Language Models

Liu, Y., Han, T., Ma, S., Zhang, J., Yang, Y., Tian, J., He, H., Li, A., He, M., Liu, Z., et al. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 1,172

Summary of ChatGPT-Related research and perspective towards the future of large language models

Liu, Y., Han, T., Ma, S., Zhang, J., Yang, Y., Tian, J., He, H., Li, A., He, M., Liu, Z., et al. (2023) · Meta-Radiology

Topic ModelingNatural Language Processing Techniques

Cited by 855

A generalist vision-language foundation model for diverse biomedical tasks

Zhang, K., Zhou, R., Adhikarla, E., Yan, Z., Liu, Y., Yu, J., Liu, Z., Chen, X., Davison, B. D., Ren, H., et al. (2024) · Nature Medicine

Multimodal Machine Learning ApplicationsArtificial Intelligence in Healthcare and Education

Cited by 333

Evaluating Large Language Models on a Highly-specialized Topic, Radiation Oncology Physics

Holmes, J., Liu, Z., Zhang, L., Ding, Y., Sio, T. T., McGee, L. A., Ashman, J. B., Li, X., Liu, T., Shen, J., et al. (2023) · arXiv

Artificial Intelligence in Healthcare and EducationArtificial Intelligence Applications

Cited by 190

Prompt Engineering for Healthcare: Methodologies and Applications

Wang, J., Shi, E., Yu, S., Wu, Z., Ma, C., Dai, H., Yang, Q., Kang, Y., Wu, J., Hu, H., et al. (2023) · arXiv

Topic ModelingArtificial Intelligence in Healthcare and Education

Cited by 150

Differentiate ChatGPT-generated and Human-written Medical Texts

Liao, W., Liu, Z., Dai, H., Xu, S., Wu, Z., Zhang, Y., Huang, X., Zhu, D., Cai, H., Liu, T., et al. (2023) · arXiv

Authorship Attribution and ProfilingTopic Modeling

Cited by 119

Radiology-GPT: A Large Language Model for Radiology

Liu, Z., Zhong, A., Li, Y., Yang, L., Ju, C., Wu, Z., Ma, C., Shu, P., Chen, C., Kim, S., et al. (2023) · arXiv

Artificial Intelligence in Healthcare and EducationMultimodal Machine Learning Applications

Cited by 59

Potential of multimodal large language models for data mining of medical images and free-text reports

Zhang, Y., Pan, Y., Zhong, T., Dong, P., Xie, K., Liu, Y., Jiang, H., Wu, Z., Liu, Z., Zhao, W., et al. (2024) · Meta-Radiology

Multimodal Machine Learning ApplicationsArtificial Intelligence in Healthcare and Education

Cited by 52

Multimodal Approaches for Alzheimer’s Detection Using Patients’ Speech and Transcript

Cai, H., Huang, X., Liu, Z., Liao, W., Dai, H., Wu, Z., Zhu, D., Ren, H., Li, Q., Liu, T., et al. (2023) · Lecture Notes in Computer Science

Dementia and Cognitive Impairment ResearchSpeech Recognition and Synthesis

Cited by 22

A Comprehensive Review of Multimodal Large Language Models: Performance and Challenges Across Different Tasks

Wang, J., Jiang, H., Liu, Y., Ma, C., Zhang, X., Pan, Y., Liu, M., Gu, P., Xia, S., Chen, L., et al. (2024) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 21

Polaris: A Safety-focused LLM Constellation Architecture for Healthcare

Mukherjee, S., Gamble, P., Ausin, M. S., Kant, N., Aggarwal, K., Manjunath, N., Datta, D., Liu, Z., Ding, J., Busacca, S., et al. (2024) · arXiv

Artificial Intelligence in Healthcare and EducationSpeech and dialogue systems

Cited by 17

CE-GAN: community evolutionary generative adversarial network for Alzheimer's disease risk prediction

Bi, X.-A., Yang, Z., Huang, Y., Xing, Z., Xu, L., Wu, Z., Liu, Z., Li, X., & Liu, T. (2024) · IEEE Transactions on Medical Imaging

Dementia and Cognitive Impairment ResearchFunctional Brain Connectivity Studies

Cited by 16