Hao Tang

Affiliations: 
2010 University of Illinois, Urbana-Champaign, Urbana-Champaign, IL 
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"Hao Tang"
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Du Y, Liu L, Yan W, et al. (2023) The anticancer mechanisms of exopolysaccharide from Weissella cibaria D-2 on colorectal cancer via apoptosis induction. Scientific Reports. 13: 21117
Li Z, Tang H, Peng Z, et al. (2023) Knowledge-Guided Semantic Transfer Network for Few-Shot Image Recognition. Ieee Transactions On Neural Networks and Learning Systems
Li Y, Zeng L, Li Z, et al. (2020) Emergency trauma care during the outbreak of corona virus disease 2019 (COVID-19) in China. World Journal of Emergency Surgery : Wjes. 15: 33
Peng Y, Tang H, Meng X, et al. (2020) Histological grades of rectal cancer: whole-volume histogram analysis of apparent diffusion coefficient based on reduced field-of-view diffusion-weighted imaging. Quantitative Imaging in Medicine and Surgery. 10: 243-256
Peng Y, Tang H, Hu X, et al. (2019) Rectal Cancer Invasiveness: Whole-Lesion Diffusion-Weighted Imaging (DWI) Histogram Analysis by Comparison of Reduced Field-of-View and Conventional DWI Techniques. Scientific Reports. 9: 18760
Wang Y, Hu D, Yu H, et al. (2018) Comparison of the Diagnostic Value of Monoexponential, Biexponential, and Stretched Exponential Diffusion-weighted MRI in Differentiating Tumor Stage and Histological Grade of Bladder Cancer. Academic Radiology
Li YX, Wang JL, Gao M, et al. (2016) Celecoxib-erlotinib combination delays growth and inhibits angiogenesis in EGFR-mutated lung cancer. American Journal of Cancer Research. 6: 1494-510
Wang YC, Hu DY, Hu XM, et al. (2016) Assessing the Early Response of Advanced Cervical Cancer to Neoadjuvant Chemotherapy Using Intravoxel Incoherent Motion Diffusion-weighted Magnetic Resonance Imaging: A Pilot Study. Chinese Medical Journal. 129: 665-671
Tang H, Chu SM, Hasegawa-Johnson M, et al. (2012) Partially supervised speaker clustering. Ieee Transactions On Pattern Analysis and Machine Intelligence. 34: 959-71
Tang H, Hasegawa-Johnson M, Huang T. (2010) A novel vector representation of stochastic signals based on adapted ergodic HMMs Ieee Signal Processing Letters. 17: 715-718
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