Results 181 to 190 of about 404,815 (264)

Interpretable Machine Learning Framework for Nb─Si Based Alloy Design with Enhanced Fracture Toughness

Advanced Science, EarlyView.
An interpretable machine learning framework integrating SHAP and PDP analysis identifies critical design descriptors from 139 physicochemical features for Nb─Si alloys. The framework achieves <7% prediction error and guides the discovery of Nb38.5Ti38.5Si3Zr18V2 alloy with 22.791 MPa·m1/2 fracture toughness, breaking the 20 MPa·m1/2 barrier.
Dezhi Chen, Chao Xu, Jingyue Yu, Qi Wang, Hongze Fang, Shuo Yin, Turab Lookman, Ruirun Chen   +7 more
wiley   +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

BRMDA: prediction model for potential microbe-drug associations based on bilinear attention networks and random forest. [PDF]

Front Genet
Yu G, Chen F, Chen H, Tang S, Liang M, Liu X, Zeng B, Wang L.   +7 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

Risk factors for PICC-associated phlebitis in preterm infants using random forest algorithm. [PDF]

Eur J Med Res
Sun X, Xu W, Wang Q, Gu R, Ding P, Li J, Zhang A, Liu B.   +7 more
europepmc   +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

Application of XGBoost and Random Forest algorithms for body weight prediction in Blackbelly sheep using biometric measurements. [PDF]

BMC Vet Res
Delgado MÁG, Tırınk C, Parra-Cortés RI, Martínez IV, Gomez-Vazquez A, Cruz-Hernandez A, Camacho-Pérez E, Dzib-Cauich DA, Önder H, Şen U, Chekirov K, Aksoy Y, Çelik HT, Odu O, Chay-Canul AJ.   +14 more
europepmc   +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

A PCA-random forest pipeline for high-resolution SNP-based cultivar discrimination in Leymus chinensis. [PDF]

BMC Plant Biol
Kong C, Hu S, Tian L, Chen S.
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