一、个人基本情况

   陈珂，副教授，博士，毕业于宁波诺丁汉大学，现任温州商学院软件工程学院教师。

二、研究方向

基于图像识别的医学人工智能应用

三、发表论文

1. Chen, K., Weng, Y., Hosseini, A. A., Dening, T., Zuo, G., & Zhang, Y. (2024). A comparative study of GNN and MLP-based machine learning for the diagnosis of Alzheimer's Disease involving data synthesis. Neural Networks, 169, 442-452.

2. Chen, K., Weng, Y., Huang, Y., Zhang, Y., Dening, T., Hosseini, A. A., & Xiao, W. (2024). A multi‐view learning approach with diffusion model to synthesize FDG PET from MRI T1WI for diagnosis of Alzheimer's disease. Alzheimer's & Dementia.

3. Zhang, Y., Chen, K., Weng, Y., Chen, Z., Zhang, J., & Hubbard, R. (2022). An intelligent early warning system of analyzing Twitter data using machine learning on COVID-19 surveillance in the US. Expert systems with applications, 198, 116882.

4. Chen, K., Hosseini, A. A., Weng, Y., Dening, T., & Zuo, G. (2023). Two‐stage diffusion model deriving FDG‐PET from T1 Weighted Magnetic Resonance Images for diagnosis of Alzheimer's disease. Alzheimer's & Dementia, 19, e076076.

5. Chen, K., Weng, Y., Dening, T., Hosseini, A. A., & Zuo, G. (2024). Brain Connectome Graphs based Machine Learning for Diagnosis of Alzheimer’s Disease. Alzheimer's & Dementia, 20, e090237.

6. Zhang, J., Chen, K., & Weng, Y. (2024). Synthesis of Healthy Tissue Within Tumor Area via U-Net. In U. Baid, R. Dorent, S. Malec, M. Pytlarz, R. Su, N. Wijethilake, S. Bakas, & A. Crimi (Eds.), Brain Tumor Segmentation, and Cross-Modality Domain Adaptation for Medical Image Segmentation (pp. 233-240). Cham: Springer Nature Switzerland. 

四、知识产权

     1. 翁莹，陈珂，张一名，一种基于可解释人工智能的外科手术技能评级方法与系统, CN114170437B(公开号)，CN202111287603.0(申请号).