Results 251 to 260 of about 86,959 (305)

Improving dengue fever predictions in Taiwan based on feature selection and random forests. [PDF]

BMC Infect Dis
Kuo CY, Yang WW, Su EC.
europepmc   +1 more source

Topology‐Aware Deep Learning on Higher‐Order Structures for Drug Response Prediction

Advanced Science, EarlyView.
We present TopDr, a topology‐aware deep learning framework that encodes both drugs and cell lines as multiscale simplicial complexes, capturing interactions at the 0‐, 1‐, and 2‐simplex levels. By jointly integrating local higher‐order neighborhoods and global topological structures, TopDr generates enriched representations for sensitivity prediction ...
Cong Shen, Guancen Lin, Chuan‐Shen Hu, Yong Wang   +3 more
wiley   +1 more source

Using random forests to uncover the predictive power of distance-varying cell interactions in tumor microenvironments. [PDF]

PLoS Comput Biol
VanderDoes J, Marceaux C, Yokote K, Asselin-Labat ML, Rice G, Hywood JD.   +5 more
europepmc   +1 more source

How Advanced Artificial Intelligence Technologies Shape Drug–Drug and Drug–Target Interaction Modeling

Advanced Science, EarlyView.
This review explores the convergence of artificial intelligence technologies in modeling drug–drug and drug–target interactions. By evaluating advanced feature engineering, architectural innovations, and learning paradigms reveals shared evolutionary trends and critical challenges, such as cold‐start settings and shortcut learning.
Xin Sun, Tong Wang
wiley   +1 more source

mTORC2 Phosphorylation of GSDME‐N Drives Cullin4B‐Mediated Proteasomal Degradation to Suppress Pyroptosis and Confer Radioresistance in Small Cell Lung Cancer

Advanced Science, EarlyView.
Radioresistance severely limits the efficacy of therapies for small cell lung cancer (SCLC). This study reveals a novel mechanism of resistance driven by the active suppression of pyroptosis. Specifically, the mTORC2 complex directly phosphorylates GSDME‐N and promotes its CUL4B‐mediated ubiquitination and proteasomal degradation.
Qing‐qing Xu, Ci‐ming Sun, Sui‐xian Zhang, Rui Li, Chen‐fei Wu, Zai‐shan Lin, Li Li, Run‐zhe Chen, Qi‐wen Li, Yuan‐yuan Chen, Xuan Li, Ming Chen   +11 more
wiley   +1 more source

Artificial Intelligence‐Based Body Composition Analysis Reveals Sex‐Specific Prognostic Markers and Their Clinical Value in Gastric Cancer: A Multicenter Study

Advanced Science, EarlyView.
This study applied AI to quantify multidimensional body composition from CT images in gastric cancer and healthy controls. Distinct sex‐specific patterns and disease‐related alterations were identified and were associated with survival. Higher muscle and fat measures were linked to improved outcomes.
Tianxiang Li, Tingting Liu, Qian Yang, Zhiqing Zhang, Xiaofang Guo, Xiang Wang, Yihan Zhang, Limin Ge, Yu Su, Wenjun Wu, Weihua Guo, Zheng Wang, Lian Yang, Yanfeng Niu   +13 more
wiley   +1 more source

Random forests with parametric entropy-based information gains for classification and regression problems. [PDF]

PeerJ Comput Sci
Ignatenko V, Surkov A, Koltcov S.
europepmc   +1 more source

Beyond d‐Band Catalysis: A Critical Review and Descriptor Framework for Rare‐Earth Engineering in Lithium–Sulfur Batteries

Advanced Science, EarlyView.
Rare‐earth catalysts regulate lithium–sulfur battery chemistry through f‐orbital–mediated interactions, enabling simultaneous polysulfide adsorption and catalytic conversion on conductive carbon hosts. This synergistic control suppresses the shuttle effect, accelerates redox kinetics, and guides stable Li2S nucleation, providing a mechanistic framework
Fan Wang, Shihzad Shakil, Guozhi Wu, Jiarui Huang, Hanhui Lei, Terence Xiaoteng Liu   +5 more
wiley   +1 more source

AI-driven discovery of blood xenobiotic biomarkers in neovascular age-related macular degeneration using iterative random forests. [PDF]

Graefes Arch Clin Exp Ophthalmol
Künzel SE, Frentzel DP, Flesch LTM, Knecht VA, Rübsam A, Dreher F, Schütte M, Dubrac A, Lange B, Yaspo ML, Lehrach H, Joussen AM, Zeitz O.   +12 more
europepmc   +1 more source

Machine Learning Accelerated Non‐Adiabatic Molecular Dynamics Elucidates Local Polarization Effects on Non‐radiative Recombination in Halide Perovskites

Advanced Science, EarlyView.
This work proposes and constructs the Hefei‐NAMD‐S framework based on machine learning stacked models to investigate the relationship between local polarization and non‐radiative recombination. The results indicate that, compared with A‐site local polarization, B‐site local polarization shows a more evident association with the non‐radiative ...
Bing Yang, Xiaoli Wei, Bo Cai, Yan Yang, Xinghai Zhu, Yi Liu, Junmin Xia, Lihui Liu, Kun Cao, Wei Shen, Pengfei Xia, Shufen Chen, Siyu Chen, Jin Zhao   +13 more
wiley   +1 more source