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Nano Letters|September 20, 2024
Automated High-Throughput Atomic Force Microscopy Single-Cell Nanomechanical Assay Enabled by Deep Learning-Based Optical Image RecognitionRui Xiao, Yanzhu Zhang, Mi LiNanoscale|December 5, 2025
High-throughput atomic force microscopy measurements reveal mechanical signatures of cell mixtures for liquid biopsyRui Xiao, Xiaoqun Qi, Yin Li, et al.ISA Transactions|April 9, 2017
Single image super-resolution using self-optimizing mask via fractional-order gradient interpolation and reconstructionQi Yang, Yanzhu Zhang, Tiebiao Zhao, et al.Frontiers in Oncology|June 10, 2026
Hybrid deep feature and machine learning framework for classification of thyroid nodules in ultrasound imagesDingnan Zhang, Bo Li, Hao Ju, et al.Artificial Intelligence in Medicine|November 26, 2025
A labeled ophthalmic ultrasound dataset with medical report generation based on cross-modal deep learningJing Wang, Junyan Fan, Meng Zhou, et al.Eye (London, England)|August 18, 2023
Applying deep learning to recognize the properties of vitreous opacity in ophthalmic ultrasound imagesLi Feng, Yanzhu Zhang, Wei Wei, et al.Carbohydrate Polymers|May 29, 2018
Investigation of composition, structure and bioactivity of extracellular polymeric substances from original and stress-induced strains of Thraustochytrium striatumRui Xiao, Xi Yang, Mi Li, et al.Journal of the Science of Food and Agriculture|October 10, 2025
Functional food potential of Anoectochilus roxburghii aqueous extract: UPLC-MS profiling and in vivo efficacy in type 2 diabetic micePing Li, Beibei Ran, Zongshuo Li, et al.Journal of Microscopy|March 4, 2023
Combining atomic force microscopy with complementary techniques for multidimensional single-cell analysisMi LiMicroscopy Research and Technique|December 6, 2023
Harnessing atomic force microscopy-based single-cell analysis to advance physical oncologyMi LiPageof 158