Results 201 to 210 of about 106,055 (260)
Metaheuristic-enhanced deep learning for monthly pan evaporation prediction under limited climatic data. [PDF]
Kisi O +5 more
europepmc +1 more source
The authors evaluated six machine‐learned interatomic potentials for simulating threshold displacement energies and tritium diffusion in LiAlO2 essential for tritium production. Trained on the same density functional theory data and benchmarked against traditional models for accuracy, stability, displacement energies, and cost, Moment Tensor Potential ...
Ankit Roy +8 more
wiley +1 more source
Biomass-Derived Activated Carbon for Congo Red Dye Adsorption: Machine-Learning-Based Prediction and Comparative Evaluation. [PDF]
Sudarsan S, Vinayagam R, Selvaraj R.
europepmc +1 more source
A machine learning method, opt‐GPRNN, is presented that combines the advantages of neural networks and kernel regressions. It is based on additive GPR in optimized redundant coordinates and allows building a representation of the target with a small number of terms while avoiding overfitting when the number of terms is larger than optimal.
Sergei Manzhos, Manabu Ihara
wiley +1 more source
Prediction of Chronic Kidney Disease Based on Simulated Serum Analysis by Vibrational Spectroscopy. [PDF]
Serrano D +3 more
europepmc +1 more source
Predictive models successfully screen nanoparticles for toxicity and cellular uptake. Yet, complex biological dynamics and sparse, nonstandardized data limit their accuracy. The field urgently needs integrated artificial intelligence/machine learning, systems biology, and open‐access data protocols to bridge the gap between materials science and safe ...
Mariya L. Ivanova +4 more
wiley +1 more source
Accurate surgery time prediction (ASTP) strategy based on artificial intelligence techniques. [PDF]
El-Balka RM, Rabie AH, Saleh AI, Sakr N.
europepmc +1 more source
Machine Learning Driven Inverse Design of Broadband Acoustic Superscattering
Multilayer acoustic superscatterers are designed using machine learning to achieve broadband superscattering and strong sound insulation. By incorporating a weighted mean absolute error into the loss function, the forward and inverse neural networks accurately map structural parameters to spectral responses.
Lijuan Fan, Xiangliang Zhang, Ying Wu
wiley +1 more source
Quality control of opportunistic multi-energy CT bone mineral density quantification. [PDF]
Thompson EA +5 more
europepmc +1 more source
This article implements a unified human digital twin framework that integrates cutting edge actuation, sensing, simulation, and bidirectional feedback capability. The approach includes integrating multimodal sensing, AI, and biomechanical simulation into one compact system.
Tajbeed Ahmed Chowdhury +4 more
wiley +1 more source

