Wei Zhao
Orcid: 0000-0002-8520-2087Affiliations:
- Central South University, Second Xiangya Hospital, Department of Radiology, Changsha, China
- Central South University, Clinical Research Center for Medical Imaging in Hunan Province, Changsha, China
- Fudan University, Shanghai, China (PhD 2019)
According to our database1,
Wei Zhao authored at least 19 papers
between 2020 and 2026.
Collaborative distances:
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Timeline
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Bibliography
2026
ChatRadio-Valuer: A Chat Large Language Model for Generalizable Radiology Impression Generation on Multi-Institution and Multi-System Data.
IEEE Trans. Biomed. Eng., March, 2026
2024
Neural Comput. Appl., July, 2024
GMILT: A Novel Transformer Network That Can Noninvasively Predict EGFR Mutation Status.
IEEE Trans. Neural Networks Learn. Syst., June, 2024
Medical Image Anal., 2024
3D-CT-GPT: Generating 3D Radiology Reports through Integration of Large Vision-Language Models.
CoRR, 2024
Proceedings of the International Conference on Computer Vision and Deep Learning, 2024
Strong Multimodal Representation Learner through Cross-domain Distillation for Alzheimer's Disease Classification.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2024
2023
IEEE Trans. Biomed. Eng., December, 2023
Anomaly detection for streaming data based on grid-clustering and Gaussian distribution.
Inf. Sci., August, 2023
ChatRadio-Valuer: A Chat Large Language Model for Generalizable Radiology Report Generation Based on Multi-institution and Multi-system Data.
CoRR, 2023
2022
IEEE Trans. Medical Imaging, 2022
Automated Diagnosis of COVID-19 Using Deep Supervised Autoencoder With Multi-View Features From CT Images.
IEEE ACM Trans. Comput. Biol. Bioinform., 2022
2021
SCOAT-Net: A novel network for segmenting COVID-19 lung opacification from CT images.
Pattern Recognit., 2021
Synergistic learning of lung lobe segmentation and hierarchical multi-instance classification for automated severity assessment of COVID-19 in CT images.
Pattern Recognit., 2021
A novel multiple instance learning framework for COVID-19 severity assessment via data augmentation and self-supervised learning.
Medical Image Anal., 2021
Expert Syst. Appl., 2021
2020
Synergistic Learning of Lung Lobe Segmentation and Hierarchical Multi-Instance Classification for Automated Severity Assessment of COVID-19 in CT Images.
CoRR, 2020
Severity Assessment of Coronavirus Disease 2019 (COVID-19) Using Quantitative Features from Chest CT Images.
CoRR, 2020