Results 141 to 150 of about 160,416 (217)

Forecasting under-five stunting in Ethiopia using classical and machine learning time series models. [PDF]

PLoS One
Gessese RT, Kelkay JM, Arage FG, Tsegaw TK, Tadese ZB, Alemayehu MA, Taye EA, Alemu EA.   +7 more
europepmc   +1 more source

Magnetoelectric Nanoparticle‐Based Wireless Brain–Computer Interface: Underlying Physics and Projected Technology Pathway

Advanced Science, EarlyView.
Magnetoelectric nanoparticles (MENPs) enable fully wireless, minutely invasive neuromodulation, and potentially neural recording, by converting magnetic into electric and, conversely, electric into magnetic fields, respectively, at high spatiotemporal resolution.
Elric Zhang, Max Shotbolt, Mostafa Abdel‐Mottaleb, Shawnus Chen, Victoria Andre, Jieyuan Tian, Jonathan Shulgach, Max Murphy, Brian Noga, Ping Liang, Darcy Griffin, Douglas Weber, Marta Pardo, Salvador Pane, Sakhrat Khizroev   +14 more
wiley   +1 more source

Survival prediction in colorectal cancer liver metastases using machine learning with SHAP-based interpretation. [PDF]

Front Oncol
Li N, Dong B, Liang Y, Liu L, Wang X, Zhang C, Hao S.   +6 more
europepmc   +1 more source

Integrating Machine Learning With Constant‐Potential Simulation to Unravel Charge‐Transfer Mechanisms in Electrochemical Nitrogen Fixation

Advanced Science, EarlyView.
Integrating interpretable machine learning with the fixed‐potential method reveals a novel mechanism: the catalytic activity of the electrochemical nitrogen reduction reaction is governed by partial charge transfer, induced by variations in the intermediate potential of zero charge under constant potential.
Yufei Xue, Dushuo Feng, Yuefei Zhang, Yang Zhang, Yalong Jiao, Aijun Du, Guoping Gao   +6 more
wiley   +1 more source

Evaluating machine learning algorithms at predicting developmental trajectories using sequential dataset truncation of voluntary alcohol consumption in adolescent mice. [PDF]

PLoS One
Yu N, Buyske S, Qureshi U, Yu L.
europepmc   +1 more source

Unifying Composition and Process Design: A Heterogeneous Graph Neural Network for Discovering High‐Performance Cu Alloys

Advanced Science, EarlyView.
By overcoming the fixed‐path limitations of conventional machine learning, a heterogeneous graph neural network fundamentally reconstructs material data representation. Integrating variable processing sequences with intrinsic elemental features, this framework enables exploratory optimization across high‐dimensional spaces.
Jie Yin, Qian Lei, Wei Yan, Yue Li, Tong Xie, Shuang Zhou, Chong Wang, Bram Hoex, Qiang Long, Caoyang Jiang, Min Song, Zhou Li, Zhangwei Wang   +12 more
wiley   +1 more source

Machine learning-based model for prediction of carbamazepine- and allopurinol-induced severe cutaneous adverse reactions in Vietnamese. [PDF]

World Allergy Organ J
Nguyen NT, Tran MH, Vu HQ, Duong VC, Nguyen TMN, Hoang OT, Mai VNA, Can TT, Do NQ, Le Thi Minh H, Nguyen NN, Vu Thi H, Vu MT, Nguyen AQ, Pham YTH, Nguyen KV, Le L, van Nunen S, Craig TJ, Chu HC, Vo NS, Nguyen DV.   +21 more
europepmc   +1 more source

High‐Throughput Data Generation and Transfer Learning Enabled Microstructure‐Property Integrated Design of Nickel‐Based Powder Metallurgy Superalloy

Advanced Science, EarlyView.
An integrated transfer learning framework integrates CALPHAD simulations, diffusion‐multiple experiments, and literature data to predict long‐term microstructural stability and short‐term mechanical properties of Ni‐based powder metallurgy superalloys. Based on these model predictions, a high‐performance, low‐density alloy, USTB‐PM750, is designed from
Zixin Li, Hongtao Zhang, Zichao Peng, Yuheng Zhang, Qian Lv, Yihuan Cao, Xuqing Wang, Huadong Fu, Jianxin Xie   +8 more
wiley   +1 more source

Geospatial variation and machine learning approaches to predict open defecation practice in Zambia. [PDF]

PLoS One
Birlie AA, Meshesha NA, Tizie SB, Wondie SG, Teshome SG, Bedada TD, Muluneh AA, Eticha BL, Dube GN, Wodessa G, Mengistie MB.   +10 more
europepmc   +1 more source