Shenzhen Technology University
Relevante Arbeiten
Meistzitierte Publikationen im Bereich Gesundheit & MedTech
Review and classification of AI-enabled COVID-19 CT imaging models based on computer vision tasks
Haseeb Hassan, Zhaoyu Ren, Huishi Zhao et al.
2021 · 63 Zit.
Supervised and weakly supervised deep learning models for COVID-19 CT diagnosis: A systematic review
Haseeb Hassan, Zhaoyu Ren, Chengmin Zhou et al.
2022 · 48 Zit.
Novel Survival Features Generated by Clinical Text Information and Radiomics Features May Improve the Prediction of Ischemic Stroke Outcome
Yingwei Guo, Yingjian Yang, Fengqiu Cao et al.
2022 · 18 Zit.
Technologies evolution in robot-assisted fracture reduction systems: a comprehensive review
Wei Kou, Peiqing Zhou, Jihong Lin et al.
2023 · 16 Zit.
The next big thing: role of ChatGPT in personal knowledge management challenges and opportunities for knowledge workers across diverse disciplines
Sumaira Nazeer, Muhammad Saleem Sumbal, Gang Liu et al.
2023 · 16 Zit.
Achieving fair medical image segmentation in foundation models with adversarial visual prompt tuning
Yuqi Li, Yanli Li, Kai Zhang et al.
2025 · 12 Zit.
Using Deep Neural Network to Diagnose Thyroid Nodules on Ultrasound in Patients With Hashimoto’s Thyroiditis
Yiqing Hou, Chao Chen, Lu Zhang et al.
2021 · 12 Zit.
From Trust in Automation to Trust in AI in Healthcare: A 30-Year Longitudinal Review and an Interdisciplinary Framework
Kelvin K. L. Wong, Yong Oun Han, Yifeng Cai et al.
2025 · 8 Zit.
Comparison of six machine learning methods for differentiating benign and malignant thyroid nodules using ultrasonographic characteristics
Jianguang Liang, Tiantian Pang, Weixiang Liu et al.
2023 · 6 Zit.
Leveraging Ensemble Models and Follow-up Data for Accurate Prediction of mRS Scores from Radiomic Features of DSC-PWI Images
Mazen M. Yassin, Asim Zaman, Jiaxi Lu et al.
2024 · 5 Zit.
Fed-DNN-Debugger: Automatically Debugging Deep Neural Network Models in Federated Learning
Shaoming Duan, Chuanyi Liu, Peiyi Han et al.
2023 · 4 Zit.
THE-TAFL: Transforming Healthcare Edge with Transformer-based Adaptive Federated Learning and Learning Rate Optimization
Farhan Ullah, Nazeeruddin Mohammad, Leonardo Mostarda et al.
2025 · 4 Zit.
Transformative Deep Neural Network Approaches in Kidney Ultrasound Segmentation: Empirical Validation with an Annotated Dataset
Rashid Khan, Chuda Xiao, Yang Liu et al.
2024 · 4 Zit.
Optimizing acute ischemic stroke outcome prediction by integrating radiomics features of DSC-PWI and perfusion parameter maps
Huihui Yang, Yingwei Guo, Jiaxi Lu et al.
2025 · 3 Zit.
Artificial Intelligence for Bone: Theory, Methods, and Applications
Dongfeng Yuan, Haicang Zhang, Liping Tong et al.
2025 · 3 Zit.