Results 181 to 190 of about 41,060,851 (256)
A Comprehensive Comparative Study of Active Learning Schemes for Nanophotonics Design
Active learning (AL) strategies are benchmarked for the binary design of planar multilayer nanophotonic structures. Factorization machines combined with quantum annealing (QA) become effective as dimensionality increases. Hybrid QA provides the strongest results for 100‐layer problems, highlighting the importance of optimization method selection in ...
Serang Jung +10 more
wiley +1 more source
With the downstream filter held fixed, text‐derived composition representations produce distinct screening outcomes across 14 electrocatalyst libraries. Embedding model and composition encoding control the trade‐off between candidate reduction and preservation of the best measured current.
Lei Zhang, Markus Stricker
wiley +1 more source
An ultra‐fast small‐sample AI consensus pipeline combines co‐folding and docking to target structure‐lacking p53 monomers. Its optimal mini‐protein binder shows robust interfacial affinity and promising druggability, supplying unprecedented antitumor p53 templates.
Ningyao Li +9 more
wiley +1 more source
Current Standards of Monitoring Models in Healthcare Settings
AI/ML‐enabled medical devices are entering clinical practice faster than monitoring standards mature. This review highlights gaps in postmarket surveillance, limited use of predetermined change‐control plans, and the need for ongoing performance tracking, drift detection, explainability, and workflow‐aware governance to support safer, more reliable ...
Alan Kay +5 more
wiley +1 more source
We present CatTransVAE, a catalyst‐specialized chemical language model (CLM) built on a transformer variational autoencoder (VAE), developed through pretraining on general compounds followed by fine‐tuning on diverse catalyst databases. A template‐guided generation framework is introduced to enable controlled catalyst design under structural ...
Apakorn Kengkanna, Masahito Ohue
wiley +1 more source
Trained immunity in inflammatory bone disease: a bibliometric and literature-level text-mining analysis. [PDF]
Zhao Z +8 more
europepmc +1 more source
Crystal Structure Prediction of Inorganic Materials: A Benchmark and Modern Evaluation
Predicting a crystal’s structure from composition alone is a long‐standing challenge in materials discovery. The CSP180 benchmark of 180 inorganic crystals evaluates thirteen crystal structure prediction algorithms requiring no density functional theory (DFT) against DFT‐based baselines across twelve metrics.
Lai Wei +9 more
wiley +1 more source
Artificial intelligence research in school leadership and management: a text mining-based computational literature review and future directions. [PDF]
Karaköse T +4 more
europepmc +1 more source
A Generative AI Framework to Predict Cardiomyocyte Contraction Function From Single Static Images
A single static hiPSC‐cardiomyocyte image is fed into a U‐Net‐GAN framework, which directly predicts a pixel‐resolved contraction heatmap without time‐lapse imaging. StyleGAN2‐generated synthetic cell–heatmap pairs augment training, improving prediction fidelity (SSIM = 0.84).
Andrew Kowalczewski +5 more
wiley +1 more source
Particle Swarm Optimization as a Noise‐Tolerant Strategy for High‐Entropy Alloy Research
A customized particle swarm optimization algorithm is benchmarked against batch Bayesian optimization across four high‐entropy alloy oxygen‐reduction landscapes. While both methods locate the global optimum comparably under noise‐free conditions, Bayesian optimization’s surrogate model tends to overfit noisy data.
Ahmad Tirmidzi +2 more
wiley +1 more source

