Binary classification of signal and background triggers of a transition edge sensor using convolutional neural networks. [PDF]
Rivasto E +7 more
europepmc +1 more source
Multi‐View Biomedical Foundation Models for Molecule‐Target and Property Prediction
Molecular foundation models can provide accurate predictions for a large set of downstream tasks. We develop MMELON, an approach that integrates pre‐trained graph, image, and text foundation models and validate our multi‐view model on over 120 tasks, including GPCR binding.
Parthasarathy Suryanarayanan +17 more
wiley +1 more source
Enhancing myocardial infarction detection with vectorcardiography: fusion-based comparative analysis of machine learning methods. [PDF]
Vondrak J, Penhaker M.
europepmc +1 more source
His‐MMDM: Multi‐Domain and Multi‐Omics Translation of Histopathological Images with Diffusion Models
His‐MMDM is a diffusion model‐based framework for scalable multi‐domain and multi‐omics translation of histopathological images, enabling tasks from virtual staining, cross‐tumor knowledge transfer, and omics‐guided image editing. ABSTRACT Generative AI (GenAI) has advanced computational pathology through various image translation models.
Zhongxiao Li +13 more
wiley +1 more source
Machine Learning Prediction of Analyte-Induced Fluorescence Perturbations in DNA-Functionalized Carbon Nanotubes. [PDF]
Chakraborty S +4 more
europepmc +1 more source
Machine learning‐assisted surface‐enhanced Raman spectroscopy analysis of exosomal sialic acid for ovarian cancer diagnosis, as well as independent monitoring of exosomal sialic acid expression levels across different treatment periods, reveals a potential correlation with treatment response.
Lili Cong +6 more
wiley +1 more source
A novel method of bayesian genetic optimization on automated hyperparameter tuning. [PDF]
Li Q +4 more
europepmc +1 more source
Generating Dynamic Structures Through Physics‐Based Sampling of Predicted Inter‐Residue Geometries
While static structure prediction has been revolutionized, modeling protein dynamics remains elusive. trRosettaX2‐Dynamics is presented to address this challenge. This framework leverages a Transformer‐based network to predict inter‐residue geometric constraints, guiding conformation generation via physics‐based iterative sampling. The resulting method
Chenxiao Xiang +3 more
wiley +1 more source
Deep Learning for Predicting Late-Onset Breast Cancer Metastasis: The Single-Hyperparameter Grid Search (SHGS) Strategy for Meta-Tuning a Deep Feed-Forward Neural Network. [PDF]
Zhou Y, Arora-Jain O, Jiang X.
europepmc +1 more source
This study combines full‐field tomography with diffraction mapping to quantify radial (ε002$\varepsilon _{002}$) and axial (ε100$\varepsilon _{100}$) lattice strain in wrinkled carbon‐fiber specimens for the first time. Radial microstrain gradients (−14.5 µεMPa$\varepsilon \mathrm{MPa}$−1) are found to signal damage‐prone zones ahead of failure, which ...
Hoang Minh Luong +7 more
wiley +1 more source

