Results 231 to 240 of about 1,718,101 (355)

Combining Spatial Multi‐Omics Data to Decipher Spatial Domains and Elucidate Cell Heterogeneity Based on Self‐Supervised Graph Learning

open access: yesAdvanced Science, EarlyView.
A self‐supervised multi‐view graph fusion framework integrates spatial multi‐omics, excelling in domain identification and denoising. It reconstructs spatial pseudo‐expression, jointly analyzes multi‐omics data, infers RNA velocity, predicts spatial omics features from single‐cell multi‐omics, and detects spatially dark genes and transcription factors,
Yuejing Lu   +8 more
wiley   +1 more source

An explainable convolutional neural network for the detection of drug abuse

open access: yes
The spread of Artificial Intelligence methods in many contexts is undeniable. Different models have been proposed and applied to real-world applications in sectors like economy, industry, medicine, healthcare and sports.
Paolo Pagliuca   +3 more
core  

A Portable and Dual‐Button Microneedle Device Enables Intelligent Multimodal Laser Sensing

open access: yesAdvanced Science, EarlyView.
A portable and dual‐button microneedle device enables rapid interstitial fluid sampling. Coupled with multimodal laser sensing and AI‐assisted data processing, the platform enables simultaneous molecular and elemental analysis for minimally invasive and multiplexed health assessment toward point‐of‐care diagnostics.
Yuanchao Liu   +12 more
wiley   +1 more source

MedSpectralNet: A lightweight convolutional neural network architecture for multi-modal image classification. [PDF]

open access: yesPLoS One
Afrin N   +7 more
europepmc   +1 more source

Decoding Spatial Heterogeneity and Multi‐Omics Regulation with Hierarchical Graph Learning

open access: yesAdvanced Science, EarlyView.
ABSTRACT Recent advances in spatial multi‐omics technologies have enabled the simultaneous profiling of multiple molecular layers within the same tissue slice, providing unprecedented opportunities to investigate tissue spatial organization. However, most existing computational methods identify spatial domains in a purely data‐driven manner, rarely ...
Jiazhou Chen   +6 more
wiley   +1 more source

STAID: A Self‐Refining Deep Learning Framework for Spatial Cell‐Type Deconvolution with Biologically Informed Modeling

open access: yesAdvanced Science, EarlyView.
STAID is a unified deep learning framework that couples iterative pseudo‐spot refinement with neural network training through a feedback loop and exploits gene co‐expression information to model higher‐order interactions, achieving accurate and robust cell‐type deconvolution in spatial transcriptomics.
Jixin Liu   +5 more
wiley   +1 more source

Field‐Free Spin‐Splitting‐Torque Driven Stochastic Neuron Mimicking the Neuromorphic Imagination for High‐Performance Recognition

open access: yesAdvanced Science, EarlyView.
The human brain's imagination, which enables autonomous driving hazard avoidance by completing missing visual information, relies on Gaussian‐stochastic neuron. We report the altermagnetic RuO2 spintronic neurons integrating field‐free switching and intrinsic Gaussian stochasticity, building an all‐spin ANN for high‐quality image repairing and high ...
Junwei Zeng   +9 more
wiley   +1 more source

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