Sequential multicolor fluorescence imaging in dynamic microsystems is constrained by acquisition speed and excitation dose. This study introduces a real‐time framework to reconstruct spectrally separated channels from reduced cross‐channel acquisitions (frames containing mixed spectral contributions).
Juan J. Huaroto +3 more
wiley +1 more source
Correction: Single-cell RNA-seq integrated with multi-omics reveals SERPINE2 as a target for metastasis in advanced renal cell carcinoma. [PDF]
Chen WJ +11 more
europepmc +1 more source
Cell Segmentation Beyond 2D—A Review of the State‐of‐the‐Art
Cell segmentation underpins many biological image analysis tasks, yet most deep learning methods remain limited to 2D despite the inherently 3D nature of cellular processes. This review surveys segmentation approaches beyond 2D, comparing 2.5D and fully 3D methods, analyzing 31 models and 32 volumetric datasets, and introducing a unified reference ...
Fabian Schmeisser +6 more
wiley +1 more source
Data Augmentation and Innovative Machine Learning Approaches for Classifying EEL Spectra of Transition Metals Oxides [PDF]
Del Pozo Bueno Daniel +4 more
doaj +1 more source
Interface-driven energy-independent charge extraction in GaN photocatalysts. [PDF]
Gao Y +8 more
europepmc +1 more source
Composition‐Aware Cross‐Sectional Integration for Spatial Transcriptomics
Multi‐section spatial transcriptomics demands coherent cell‐type deconvolution, domain detection, and batch correction, yet existing pipelines treat these tasks separately. FUSION unifies them within a composition‐aware latent framework, modeling reads as cell‐type–specific topics and clustering in embedding space.
Qishi Dong +5 more
wiley +1 more source
Depth Dependence of Electron Channeling Contrast Imaging in Gallium Nitride [PDF]
Lavallee Etienne +3 more
doaj +1 more source
Generative adversarial networks and hyperparameter-optimized XGBoost for enhanced heart disease prediction. [PDF]
Begum SS +5 more
europepmc +1 more source
Harnessing Machine Learning to Understand and Design Disordered Solids
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley +1 more source
Generative AI-Driven Discovery of Next-Generation Electrolytes for Alkali Metal Batteries. [PDF]
Pritom R, Islam MM.
europepmc +1 more source

