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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

MOMHCA-SG: a multi-head cross-attention and similar graph convolutional network framework for Alzheimer's disease cell type classification. [PDF]

Front Neurosci
Qian Y, Kong W, Wang S, Wen G, Yu Y.
europepmc +1 more source

Machine Learning Unveils Isolated‐Surrounded Pt Motifs in High‐Entropy Alloys for Superior Low‐Temperature Ammonia Oxidation

ENERGY &ENVIRONMENTAL MATERIALS, EarlyView.
A physics‐informed machine learning approach successfully decodes the complex catalytic activity of high‐entropy alloys for ammonia oxidation. By revealing a synergistic mechanism involving lattice and electronic couplings, the study identifies a superior “isolated‐surrounded” platinum motif.
Shangfeng Jiang +5 more
wiley +1 more source

Application of artificial intelligence graph convolutional network in classroom grade evaluation. [PDF]

Sci Rep
Wu S.
europepmc +1 more source

Nanophotonic Biosensors and the Paradigm of Trans‐Scale Autonomous Bio‐Integrated Diagnostics for Addressing Health Complexities

Electron, EarlyView.
Physics‐driven advances in optical nanobiosensors for rapid, miniaturized, and point‐of‐care diagnostics for next‐generation decentralized and personalized healthcare based on sensor intelligence. ABSTRACT Public health emergencies and the escalating burden of chronic diseases necessitate a paradigm shift from centralized laboratory testing to rapid ...
Vishal Chaudhary +5 more
wiley +1 more source

Dynamic Graph Convolutional Network with Dilated Convolution for Epilepsy Seizure Detection. [PDF]

Bioengineering (Basel)
Zhang X, Dai C, Guo Y.
europepmc +1 more source

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

ST-GCP: a graph convolutional network model with contrastive consistency and permutation for spatial transcriptomics. [PDF]

Brief Bioinform
Meng Y +9 more
europepmc +1 more source

Automated segmentation of postsurgical resection cavities on magnetic resonance imaging in focal epilepsy: A Multicentre Epilepsy Lesion Detection study

Epilepsia, EarlyView.
Abstract Objective Quantitative assessment of extent of tissue resection following epilepsy surgery requires accurate delineation of the resection cavity on postoperative magnetic resonance imaging (MRI). Current methods for resection cavity masking are time‐consuming and labor‐intensive, and existing automated approaches exhibit variable segmentation ...
Jieun Seo +91 more
wiley +1 more source

An algorithm for seizure detection in rodents

Epilepsia Open, EarlyView.
Abstract Objective Epilepsy animal research often relies on long‐term intracranial electroencephalographic (iEEG) recordings. Here, we describe an artificial neural network (ANN) algorithm for automatic detection of seizures. Methods The algorithm was trained on iEEG recordings of three mouse models of chronic epilepsy: (1) the pilocarpine model of ...
Lyna Kamintsky +9 more
wiley +1 more source

graph convolutional neural network
deep learning
medicine

graph convolutional networks
graph neural network