Results 241 to 250 of about 22,191,063 (377)
This work introduces a novel framework for identifying non‐small cell lung cancer biomarkers from hundreds of volatile organic compounds in breath, analyzed via gas chromatography‐mass spectrometry. This method integrates generative data augmentation and multi‐view feature selection, providing a stable and accurate solution for biomarker discovery in ...
Guancheng Ren +10 more
wiley +1 more source
CBMR: Coordinate-based meta-regression for group and covariate inference. [PDF]
Yu Y +5 more
europepmc +1 more source
This study introduces the first inverse machine learning model to predict laser powder bed fusion process parameters for targeted surface roughness of Inconel 718 parts. Unlike prior approaches, it incorporates spatial surface characteristics for improved accuracy.
Samsul Mahmood, Bart Raeymaekers
wiley +1 more source
Candidate genes for anthracnose resistance in Senegalese sorghum: a machine learning-based exploration. [PDF]
Ahn E +6 more
europepmc +1 more source
This study introduces a framework that combines graph neural networks with causal inference to forecast recurrence and uncover the clinical and pathological factors driving it. It further provides interpretability, validates risk factors via counterfactual and interventional analyses, and offers evidence‐based insights for treatment planning ...
Jubair Ahmed +3 more
wiley +1 more source
Robust Lifetime Estimation from HPGe Radiation-Sensor Time Series Using Pairwise Ratios and MFV Statistics. [PDF]
Golovko VV.
europepmc +1 more source
Cross‐Modal Characterization of Thin‐Film MoS2 Using Generative Models
Cross‐modal learning is evaluated using atomic force microscopy (AFM), Raman spectroscopy, and photoluminescence spectroscopy (PL) through unsupervised learning, regression, and autoencoder models. Autoencoder models are used to generate spectroscopy data from the microscopy images.
Isaiah A. Moses +3 more
wiley +1 more source
A practice-oriented guide to statistical inference in linear modeling for non-normal or heteroskedastic error distributions. [PDF]
Rajh-Weber H, Huber SE, Arendasy M.
europepmc +1 more source
Bootstrap percolation on the stochastic block model with k communities [PDF]
Giovanni Luca Torrisi +2 more
openalex +1 more source

