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
Global Geography of Natural History Museum Specimen Holdings: A Time-Resolved Network Analysis of Mammal Collections, 1900-2020. [PDF]
Mills MW, Lassiter U.
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
Kidney anatomy: A Survey of Historical Illustrations and Methods of Depiction. [PDF]
Clarkson MD, Platt KM.
europepmc +1 more source
Autonomous AI‐Driven Design for Skin Product Formulations
This review presents a comprehensive closed‐loop framework for autonomous skin product formulation design. By integrating artificial intelligence‐driven experiment selection with automated multi‐tiered assays, the approach shifts development from trial‐and‐error to intelligent optimisation.
Yu Zhang +5 more
wiley +1 more source
Global sampling decline erodes science potential of natural history collections. [PDF]
Forbes O, Young AG, Thrall PH.
europepmc +1 more source
AI‐Driven Cancer Multi‐Omics: A Review From the Data Pipeline Perspective
The exponential growth of cancer multi‐omics data brings opportunities and challenges for precision oncology. This review systematically examines AI's role in addressing these challenges, covering generative models, integration architectures, Explainable AI for clinical trust, clinical applications, and key directions for clinical translation.
Shilong Liu, Shunxiang Li, Kun Qian
wiley +1 more source
Stress and cardiovascular disease: Testing a vigilance pathway in two contemporary theories. [PDF]
O'Neill RM +11 more
europepmc +1 more source
Interpreting How Neural Networks Infer Scatterer Geometry from Echolocation Echoes
Neural networks enable echolocation‐based shape classification but remain difficult to interpret due to their black‐box nature. This work presents a feature‐importance metric to uncover the echo regions driving decisions in shape‐specialized networks.
Ganesh U. Patil +2 more
wiley +1 more source

