Generative Models in Inorganic Crystals Discovery and Inverse Design
ENERGY &ENVIRONMENTAL MATERIALS, EarlyView.Generative inverse‐design samples from the vast inorganic crystal design space by starting from target properties such as band gap, stability, and ion transport. This Review examines the representations, generative models, and validation workflows needed to translate candidate structures into stable, potentially synthesizable materials for applications
Tao Li +5 more
wiley +1 more source
A crowdsensing platform for structural health monitoring of rural bridge infrastructure. [PDF]
Open Res EurTantaroudas ND +7 more
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Artificial intelligence for adaptive neuromodulation in drug‐resistant epilepsy
Epilepsia, EarlyView.Abstract Drug‐resistant epilepsy (DRE) affects nearly one third of people with epilepsy and is associated with substantial cognitive, psychiatric, and mortality burdens. For patients who are not candidates for resection or laser interstitial thermal therapy, neuromodulation therapies such as vagus nerve stimulation, deep brain stimulation, and ...
Amir Hossein Daraie +10 more
wiley +1 more source
Attention-Enhanced Autoencoder with Marginal-Variance-Regularized Feature Reconstruction for Imbalanced Insurance Policy-Ownership Classification. [PDF]
Entropy (Basel)Tian J, Ding Q, Li B, Yang X.
europepmc +1 more source
Frontiers in EEG as a tool for the management of pediatric epilepsy: Past, present, and future
Epilepsia Open, EarlyView.Abstract Electroencephalography (EEG) has evolved into an indispensable tool in pediatric epilepsy, fundamentally transforming the diagnosis, classification, and management of this condition. This review chronicles the historical journey of EEG from its groundbreaking inception to its current pivotal role in delineating distinct pediatric epilepsy ...
Hiroki Nariai
wiley +1 more source
AI‐based localization of the epileptogenic zone using intracranial EEG
Epilepsia Open, EarlyView.Abstract Artificial intelligence (AI) is rapidly transforming our lives. Machine learning (ML) enables computers to learn from data and make decisions without explicit instructions. Deep learning (DL), a subset of ML, uses multiple layers of neural networks to recognize complex patterns in large datasets through end‐to‐end learning.
Atsuro Daida +5 more
wiley +1 more source
Synthetic data augmentation for CT-based emphysema subtype classification: A comparative evaluation of generative and classical approaches. [PDF]
PLoS OneDietrich N, McShannon D.
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Artificial intelligence in preclinical epilepsy research: Current state, potential, and challenges
Epilepsia Open, EarlyView.Abstract Preclinical translational epilepsy research uses animal models to better understand the mechanisms underlying epilepsy and its comorbidities, as well as to analyze and develop potential treatments that may mitigate this neurological disorder and its associated conditions. Artificial intelligence (AI) has emerged as a transformative tool across
Jesús Servando Medel‐Matus +7 more
wiley +1 more source
Journal of Forecasting, EarlyView.ABSTRACT Deep learning‐based long time series forecasting (LTSF) has achieved high accuracy by effectively capturing the underlying trends, seasonality, and temporal dependencies within time series data. However, at the individual entity level, termed the low aggregation level (LAL), intermittency, irregularity, and data sparsity undermine the ...
Hanbyeol Park +5 more
wiley +1 more source
AGENTi: APCI-ESI Analyte Ionization Fidelity Pre-Screening Workflow using Multimodel Inference. [PDF]
J Chem Inf ModelKeng M, Merz KM.
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