Results 141 to 150 of about 111,097 (310)

Causal Prediction of TP53 Variant Pathogenicity Using a Perturbation‐Informed Protein Language Model

Advanced Science, EarlyView.
A TP53‐specific predictor, CaVepP53, is developed by fine‐tuning ESMC on experimentally validated variants, quantifying pathogenicity via Euclidean distances. It outperforms general‐purpose models and extends to five cancer genes, enabling interpretable variant classification for precision medicine.
Huiying Chen, Yang Zhao, Boqiang Hu, Wuke Wang, Minfang Song, Annabeth Xinyu Zhao, Xiangyang Li, Gefei Wang, Yanfen Wang, Weiyan Zheng, Xinpeng Zhang, Xia Lin, Yanbin Yin, Xingxu Huang, Jinfang Zheng, Tingbo Liang   +15 more
wiley   +1 more source

The Impact of Feature Embedding Placement in the Ansatz of a Quantum Kernel in QSVMs [PDF]

Ilmo Salmenperä, Ilmars Kuhtarskis, Arianne Meijer van de Griend, Jukka K. Nurminen   +3 more
openalex   +1 more source

Kolmogorov Width Decay and Poor Approximators in Machine Learning: Shallow Neural Networks, Random Feature Models and Neural Tangent Kernels [PDF]

, 2020
E Weinan, Stephan Wojtowytsch
openalex   +1 more source

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

Advanced 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, Tommaso Gili, Andrea Gabrielli, Maurizio Mattia   +3 more
wiley   +1 more source

Horseshoes in multidimensional scaling and local kernel methods [PDF]

, 2008
Persi Diaconis, Sharad Goel, Susan Holmes   +2 more
openalex   +1 more source

SKOOTS: Skeleton‐Oriented Object Segmentation for Mitochondria in High‐Resolution Cochlear EM Datasets

Advanced Science, EarlyView.
Skeleton‐oriented object segmentation (SKOOTS) introduces a new strategy for 3D mitochondrial instance segmentation by predicting explicit skeletons rather than relying on boundary cues. This approach enables robust analysis of densely packed organelles in large FIB‐SEM datasets.
Christopher J. Buswinka, Richard T. Osgood, Hidetomi Nitta, Artur A. Indzhykulian   +3 more
wiley   +1 more source

Demonstration of an AI-driven workflow for autonomous high-resolution scanning microscopy. [PDF]

Nat Commun, 2023
Kandel S, Zhou T, Babu AV, Di Z, Li X, Ma X, Holt M, Miceli A, Phatak C, Cherukara MJ.   +9 more
europepmc   +1 more source

Predicting Single Kernel Moisture and Protein Content of Mushroom Popcorn Using NIR Spectroscopy: Tool for Determining their Effect on Popping Performance

, 2022
Xiaorong Wu, Paul R. Armstrong, Elizabeth B. Maghirang   +2 more
openalex   +2 more sources

Neural Fields for Highly Accelerated 2D Cine Phase Contrast MRI

Advanced Science, EarlyView.
ABSTRACT 2D cine phase contrast (CPC) MRI provides quantitative information on blood velocity and flow within the human vasculature. However, data acquisition is time‐consuming, motivating the reconstruction of the velocity field from undersampled measurements to reduce scan times. In this work, neural fields are proposed as a continuous spatiotemporal
Pablo Arratia, Martin J. Graves, Mary McLean, Carolin Pirkl, Carola‐Bibiane Schönlieb, Timo Schirmer, Florian Wiesinger, Matthias J. Ehrhardt   +7 more
wiley   +1 more source

On the generalization of Tanimoto-type kernels to real valued functions. [PDF]

, 2020
Sandor Szedmak Eric Bach
openalex