Results 161 to 170 of about 675,521 (280)

High‐Fidelity Synthetic Data Replicates Clinical Prediction Performance in a Million‐Patient Diabetes Cohort

open access: yesAdvanced Science, EarlyView.
This study generates high‐fidelity synthetic longitudinal records for a million‐patient diabetes cohort, successfully replicating clinical predictive performance. However, deeper analysis reveals algorithmic biases and trajectory inconsistencies that escape standard quality metrics. These findings challenge current validation norms, demonstrating why a
Francisco Ortuño   +5 more
wiley   +1 more source

An Increasing Misalignment Between Crop Distribution and Environmental Resources Under Climate Change in China

open access: yesAdvanced Science, EarlyView.
Climate change reshapes the spatial alignment between crop production and environmental resources. Using multi‐source data and a crop model, integrated climatic, water, and soil endowments for maize and wheat are quantified and compared with harvest distributions.
Zheng'e Su   +13 more
wiley   +1 more source

A Wireless, Battery‐Free Artificial Throat Patch with Deep Learning for Emotional Speech Recognition

open access: yesAdvanced Science, EarlyView.
In this work, Xu and co‐workers develop a wireless, battery‐free artificial throat patch system (ATPS) consisting of a carbon nanotube‐based thin‐film strain sensor and a miniaturized flexible printed circuit board, to enable real‐time sensing of throat signals.
Bingxin Xu   +10 more
wiley   +1 more source

Linearizing and Forecasting: A Reservoir Computing Route to Digital Twins of the Brain

open access: yesAdvanced Science, EarlyView.
A new approach uses simple neural networks to create digital twins of brain activity, capturing how different patterns unfold over time. The method generates and recovers key dynamics even from noisy data. When applied to fMRI, it predicts brain signals and reveals distinctive activity patterns across regions and individuals, opening possibilities for ...
Gabriele Di Antonio   +3 more
wiley   +1 more source

Solid Harmonic Wavelet Bispectrum for Image Analysis

open access: yesAdvanced Science, EarlyView.
The Solid Harmonic Wavelet Bispectrum (SHWB), a rotation‐ and translation‐invariant descriptor that captures higher‐order (phase) correlations in signals, is introduced. Combining wavelet scattering, bispectral analysis, and group theory, SHWB achieves interpretable, data‐efficient representations and demonstrates competitive performance across texture,
Alex Brown   +3 more
wiley   +1 more source

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