Results 161 to 170 of about 155,735 (298)
Meta-Learning and the Full Model Selection Problem [PDF]
, 2014 When working as a data analyst, one of my daily tasks is to select appropriate tools from a set of existing data analysis techniques in my toolbox, including data preprocessing, outlier detection, feature selection, learning algorithm and evaluation ...
Sun, Quan
core
Advanced Science, EarlyView.Phase‐resolved experiments and atomistic simulations reveal asynchronous ordering behaviors in a eutectic high‐entropy alloy during isothermal annealing. Distinct defect transport mechanisms are identified in coexisting B2 and BCC phases, showing that vacancy and interstitial mediated diffusion governs phase‐dependent thermal stability.
Huiwen Yao +5 more
wiley +1 more source
Review of Classification Medical Images Using Ensemble Learning
NTU Journal of Pure SciencesMachine learning and deep learning play an important role today in the field of classification and prediction of diseases, particularly through computer-assisted medical imaging and modern devices, which aid in early disease detection, lowering the ...
Fatima Maan Abdulatif Abdulatif +1 more
doaj +1 more source
Dual-Phase Neural Networks for Feature Extraction and Ensemble Learning for Recognizing Human Health Activities [PDF]
The integration of smart devices into healthcare has led to the creation of vast amounts of sensor data, which are crucial for advancing various healthcare applications such as elderly care, lifestyle enhancement, and health monitoring.
Goyal, Puneet +7 more
core +1 more source
Mechanism‐Informed Machine Learning Enables Discovery of Oncolytic Peptides for Cancer Immunotherapy
Advanced Science, EarlyView.MISPOP integrates ensemble learning with membrane‐active physicochemical priors to identify Dermaseptin‐S9, a natural oncolytic peptide that disrupts tumor membranes, triggers immunogenic cell death, and shows strong antitumor activity. The study illustrates a mechanism‐informed route from peptide sequence data to cancer immunotherapy leads.
Wen Zhang +11 more
wiley +1 more source
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 +7 more
wiley +1 more source
AN EMPIRICAL STUDY ON CARBON PRICE PREDICTION USING STACKING ENSEMBLE MACHINE LEARNING [PDF]
Carbon pricing is an essential instrument for reducing climate change and has substantial environmental protection as a co-benefit. This paper proposes a technique for predicting the price of carbon emission futures based on a stacking ensemble machine ...
Liao, Chih-Feng;Zhang, Wang
core +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 +3 more
wiley +1 more source
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