Pathological Proliferation of CD4<sup>+</sup> T Cells in Late Presentation of HIV Infection After Antiretroviral Therapy. [PDF]
Liu H +9 more
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GelMA‐based 3D spheroids recapitulate transcriptomic and functional hallmarks of myeloid sarcoma
GelMA 5% hydrogels support the formation of myeloid leukemia spheroids that recapitulate MS‐specific features, including G1 arrest, apoptosis, and ECM‐driven transcriptomic reprogramming. The 3D model mimicked soft‐tissue‐like stiffness and oxygen conditions, and transcriptomic convergence with primary MS samples confirmed its utility as a preclinical ...
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Partial Multi-Label Feature Selection via Entropy-Weighted Multi-Scale Neighborhood Granular Label Distribution Learning. [PDF]
Cao Y +5 more
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Diffusion-MRI-Based Estimation of Cortical Architecture via Machine Learning (DECAM) in Primate Brains. [PDF]
Zhu T +7 more
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Genotype-by-environment interactions may limit the selection efficiency of chickens intended for free-range systems. [PDF]
Chaumont S +4 more
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Evaluating machine learning algorithms based on thermal imaging and milk-based parameters to identify subclinical mastitis in dairy cows. [PDF]
Paudyal S +4 more
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Mistaking Covariance for Combination in Sensorimotor Adaptation: Regression Slopes Do Not Test Additivity. [PDF]
Liddy J.
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Dynamic Changes in Exhaled Breath Glucose by Condensate Collection During Oral Glucose Tolerance Testing in Healthy Adults. [PDF]
Xu W, Zhang Q, Hong Y, Mao Z.
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Label Distribution Learning with Label Correlations on Local Samples
IEEE Transactions on Knowledge and Data Engineering, 2021Label distribution learning (LDL) is proposed for solving the label ambiguity problem in recent years, which can be seen as an extension of multi-label learning. To improve the performance of label distribution learning, some existing algorithms exploit label correlations in a global manner that assumes the label correlations are shared by all ...
Weiwei Li, Zechao Li, Sheng-Jun Huang
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