Results 151 to 160 of about 262,580 (281)
Abstract Background This study presents SIMSleepSM, a novel single‐channel electroencephalography (EEG) sleep staging model. It addresses two primary challenges: insufficient modeling of long‐range temporal dependencies combined with limited multi‐scale feature extraction, and poor accuracy in identifying the N1 stage.
Ya‐mei Xu, Ding‐Yuan An
wiley +1 more source
Free Energy Calculation Method Based on Enhanced Sampling of Diverse Protein Conformations Predicted by Artificial Intelligence. [PDF]
Aoki T, Harada R.
europepmc +1 more source
Abstract This paper presents a numerical and experimental study aimed at the modeling and dynamic characterization of the reinforced concrete structure of the Palazzetto dello Sport in Rome, designed and by Pier Luigi Nervi with Annibale Vitellozzi, and built by Nervi & Bartoli contractors in 1956‐57.
Jacopo Ciambella +2 more
wiley +1 more source
DQN‐Guided Subset‐Induced OCSVM Kernel Approximation for Imbalanced Anomaly Detection
Anomaly detection under limited normal data remains a fundamental challenge due to severe class imbalance and scarcity of anomalies. We propose a novel framework that reformulates support vector selection in One‐Class SVM as a sequential decision‐making problem.
Wenqian Yu, Jiaying Wu, Jinglu Hu
wiley +1 more source
Improving Conformational Ensembles of Folded Proteins in Go̅Martini. [PDF]
Kalutskii M +3 more
europepmc +1 more source
Enhancing generalized spectral clustering with embedding Laplacian graph regularization
Abstract An enhanced generalised spectral clustering framework that addresses the limitations of existing methods by incorporating the Laplacian graph and group effect into a regularisation term is presented. By doing so, the framework significantly enhances discrimination power and proves highly effective in handling noisy data.
Hengmin Zhang +5 more
wiley +1 more source
Boosted unsupervised feature selection for tumor gene expression profiles
Abstract In an unsupervised scenario, it is challenging but essential to eliminate noise and redundant features for tumour gene expression profiles. However, the current unsupervised feature selection methods treat all samples equally, which tend to learn discriminative features from simple samples.
Yifan Shi +5 more
wiley +1 more source
Inferring latent behavioral strategy from the representational geometry of prefrontal cortex activity. [PDF]
Qian Y, Herikstad R, Libedinsky C.
europepmc +1 more source
Clustering single-cell multi-omics data via multi-subspace contrastive learning with structural smoothness. [PDF]
Ding Y +5 more
europepmc +1 more source

