ArticleCommunications biology2023
Segmentation of human functional tissue units in support of a Human Reference Atlas.
Article in Communications biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
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
12 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.
- Vasculature segmentation in 3D hierarchical phase-contrast tomography images of human kidneys.Nature communications · 2026Pooled it
- Cell Type Populations for 3D Anatomical Structures of the Human Reference Atlas.Scientific data · 2026Article
- Fluid-Squid: DIY Multiplexed Imaging of Cells and Tissues.bioRxiv : the preprint server for biology · 2025Article
- Constructing and Using Cell Type Populations of the Human Reference Atlas.bioRxiv : the preprint server for biology · 2025Article
- Construction, Deployment, and Usage of the Human Reference Atlas Knowledge Graph.Scientific data · 2025Article
- Human BioMolecular Atlas Program (HuBMAP): 3D Human Reference Atlas construction and usage.Nature methods · 2025Article
- Construction, Deployment, and Usage of the Human Reference Atlas Knowledge Graph for Linked Open Data.bioRxiv : the preprint server for biology · 2025Article
- Functional tissue units in the Human Reference Atlas.Nature communications · 2025Article
- Human BioMolecular Atlas Program (HuBMAP): 3D Human Reference Atlas Construction and Usage.bioRxiv : the preprint server for biology · 2024Article
- Functional Tissue Units in the Human Reference Atlas.bioRxiv : the preprint server for biology · 2023Article
- Segmenting functional tissue units across human organs using community-driven development of generalizable machine learning algorithms.Nature communications · 2023Article
- Automated Segmentation of Subretinal Fluid from OCT: A Vision Transformer Approach with Cross-Validation.Ophthalmology scienceArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
15 authors at 5 institutions in 1 country.
Funding
Abstract
The Human BioMolecular Atlas Program (HuBMAP) aims to compile a Human Reference Atlas (HRA) for the healthy adult body at the cellular level. Functional tissue units (FTUs), relevant for HRA construction, are of pathobiological significance. Manual segmentation of FTUs does not scale; highly accurate and performant, open-source machine-learning algorithms are needed. We designed and hosted a Kaggle competition that focused on development of such algorithms and 1200 teams from 60 countries participated. We present the competition outcomes and an expanded analysis of the winning algorithms on additional kidney and colon tissue data, and conduct a pilot study to understand spatial location and density of FTUs across the kidney. The top algorithm from the competition, Tom, outperforms other algorithms in the expanded study, while using fewer computational resources. Tom was added to the HuBMAP infrastructure to run kidney FTU segmentation at scale-showcasing the value of Kaggle competitions for advancing research.
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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.