ArticleIEEE transactions on visualization and computer graphics2020
Facetto: Combining Unsupervised and Supervised Learning for Hierarchical Phenotype Analysis in Multi-Channel Image Data.
Article in IEEE transactions on visualization and computer graphics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
19 citing papers in PubMed.
- SEAL: Spatially-resolved Embedding Analysis with Linked Imaging Data.IEEE transactions on visualization and computer graphics · 2026Article
- SEAL : Spatially-resolved Embedding Analysis with Linked Imaging Data.bioRxiv : the preprint server for biology · 2025Article
- Closing the multichannel gap through computational reconstruction of interaction in super-resolution microscopy.Patterns (New York, N.Y.) · 2025Review
- Aardvark: Composite Visualizations of Trees, Time-Series, and Images.IEEE transactions on visualization and computer graphics · 2025Article
- MiMICRI: Towards Domain-centered Counterfactual Explanations of Cardiovascular Image Classification Models.Proceedings of the ... Conference on Fairness, Accountability, and Transparency · 2024Article
- psudo: Exploring Multi-Channel Biomedical Image Data with Spatially and Perceptually Optimized Pseudocoloring.Computer graphics forum : journal of the European Association for Computer Graphics · 2024Article
- Residency Octree: A Hybrid Approach for Scalable Web-Based Multi-Volume Rendering.IEEE transactions on visualization and computer graphics · 2024Article
- Polyphony: an Interactive Transfer Learning Framework for Single-Cell Data Analysis.IEEE transactions on visualization and computer graphics · 2023Article
- Statistical Analysis of Multiplex Immunofluorescence and Immunohistochemistry Imaging Data.Methods in molecular biology (Clifton, N.J.) · 2023Review
- Visinity: Visual Spatial Neighborhood Analysis for Multiplexed Tissue Imaging Data.IEEE transactions on visualization and computer graphics · 2023Article
- HistoML, a markup language for representation and exchange of histopathological features in pathology images.Scientific data · 2022Article
- Narrative online guides for the interpretation of digital-pathology images and tissue-atlas data.Nature biomedical engineering · 2022Review
- Deep learning-based image processing in optical microscopy.Biophysical reviews · 2022Review
- Scope2Screen: Focus+Context Techniques for Pathology Tumor Assessment in Multivariate Image Data.IEEE transactions on visualization and computer graphics · 2022Article
- ShapoGraphy: A User-Friendly Web Application for Creating Bespoke and Intuitive Visualisation of Biomedical Data.Frontiers in bioinformatics · 2022Article
- Differentiable biology: using deep learning for biophysics-based and data-driven modeling of molecular mechanisms.Nature methods · 2021Review
- Inter-Metastatic Heterogeneity of Tumor Marker Expression and Microenvironment Architecture in a Preclinical Cancer Model.International journal of molecular sciences · 2021Article
- Deep learning-based image analysis methods for brightfield-acquired multiplex immunohistochemistry images.Diagnostic pathology · 2020Article
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Facetto is a scalable visual analytics application that is used to discover single-cell phenotypes in high-dimensional multi-channel microscopy images of human tumors and tissues. Such images represent the cutting edge of digital histology and promise to revolutionize how diseases such as cancer are studied, diagnosed, and treated. Highly multiplexed tissue images are complex, comprising 10
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.