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Hong-Yu Zhou

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Articles 68
Citations 499
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Recent Articles
1.
Gao Y, Tan T, Wang X, Beets-Tan R, Zhang T, Han L, et al.
IEEE J Biomed Health Inform . 2025 Mar; PP. PMID: 40031606
Longitudinal medical imaging is crucial for monitoring neoadjuvant therapy (NAT) response in clinical practice. However, mainstream artificial intelligence (AI) methods for disease monitoring commonly rely on extensive segmentation labels to...
2.
Liu J, Yang H, Zhou H, Yu L, Liang Y, Yu Y, et al.
IEEE Trans Med Imaging . 2025 Mar; PP. PMID: 40030346
Vision foundation models have shown great potential in improving generalizability and data efficiency, especially for medical image segmentation since medical image datasets are relatively small due to high annotation costs...
3.
Lou M, Ying H, Liu X, Zhou H, Zhang Y, Yu Y
Neural Netw . 2025 Feb; 185:107228. PMID: 39908910
Automated classification of liver lesions in multi-phase CT and MR scans is of clinical significance but challenging. This study proposes a novel Siamese Dual-Resolution Transformer (SDR-Former) framework, specifically designed for...
4.
Johri S, Jeong J, Tran B, Schlessinger D, Wongvibulsin S, Barnes L, et al.
Nat Med . 2025 Jan; 31(1):77-86. PMID: 39747685
The integration of large language models (LLMs) into clinical diagnostics has the potential to transform doctor-patient interactions. However, the readiness of these models for real-world clinical application remains inadequately tested....
5.
Wang J, Wang K, Yu Y, Lu Y, Xiao W, Sun Z, et al.
Nat Med . 2024 Dec; 31(2):609-617. PMID: 39663467
In many clinical and research settings, the scarcity of high-quality medical imaging datasets has hampered the potential of artificial intelligence (AI) clinical applications. This issue is particularly pronounced in less...
6.
Gao Y, Ventura-Diaz S, Wang X, He M, Xu Z, Weir A, et al.
Nat Commun . 2024 Nov; 15(1):9613. PMID: 39511143
Multi-modal image analysis using deep learning (DL) lays the foundation for neoadjuvant treatment (NAT) response monitoring. However, existing methods prioritize extracting multi-modal features to enhance predictive performance, with limited consideration...
7.
Zhang K, Zhou H, Baptista-Hon D, Gao Y, Liu X, Oermann E, et al.
Patterns (N Y) . 2024 Sep; 5(8):101028. PMID: 39233690
The digital twin (DT) is a concept widely used in industry to create digital replicas of physical objects or systems. The dynamic, bi-directional link between the physical entity and its...
8.
Huang W, Li C, Zhou H, Yang H, Liu J, Liang Y, et al.
Nat Commun . 2024 Sep; 15(1):7620. PMID: 39223122
Recently, multi-modal vision-language foundation models have gained significant attention in the medical field. While these models offer great opportunities, they still face crucial challenges, such as the requirement for fine-grained...
9.
Chen C, Wu Y, Dai Q, Zhou H, Xu M, Yang S, et al.
IEEE Trans Pattern Anal Mach Intell . 2024 Aug; 46(12):10297-10318. PMID: 39159038
Graph Neural Networks (GNNs) have gained momentum in graph representation learning and boosted the state of the art in a variety of areas, such as data mining (e.g., social network...
10.
He T, Zhou H, Zhu M, Zhang J
Eur J Public Health . 2024 Apr; 34(4):760-765. PMID: 38607985
Background: Since the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection exhibits multi-organ damage with diverse complications, the correlation between age, gender, medical history and clinical manifestations of novel coronavirus...