ArticleProceedings of SPIE--the International Society for Optical Engineering2021
A cross-platform informatics system for the Gut Cell Atlas: integrating clinical, anatomical and histological data.
Article in Proceedings of SPIE--the International Society for Optical Engineering, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 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.
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Who cites it
12 citing papers in PubMed.
- Quantitative benchmarking of anomaly detection methods in digital pathology images.Machine Learning. Health · 2025Article
- Enhancing Clinical Data Management Through Barcode Integration and Research Electronic Data Capture: Scalable and Adaptable Implementation Study.JMIR formative research · 2025Article
- Article
- Data-driven nucleus subclassification on colon hematoxylin and eosin using style-transferred digital pathology.Journal of medical imaging (Bellingham, Wash.) · 2024Article
- Cross-scale multi-instance learning for pathological image diagnosis.Medical image analysis · 2024Article
- Cell Spatial Analysis in Crohn's Disease: Unveiling Local Cell Arrangement Pattern with Graph-based Signatures.Proceedings of SPIE--the International Society for Optical Engineering · 2024Article
- Alleviating tiling effect by random walk sliding window in high-resolution histological whole slide image synthesis.Proceedings of machine learning research · 2024Article
- Topological-Preserving Membrane Skeleton Segmentation in Multiplex Immunofluorescence Imaging.Proceedings of SPIE--the International Society for Optical Engineering · 2023Article
- Cross-scale Attention Guided Multi-instance Learning for Crohn's Disease Diagnosis with Pathological Images.Multiscale multimodal medical imaging : Third International Workshop, MMMI 2022, held in conjunction with MICCAI 2022, Singapore, September 22, 2022, proceedings · 2022Article
- MxIF Q-score: Biology-Informed Quality Assurance for Multiplexed Immunofluorescence Imaging.Medical optical imaging and virtual microscopy image analysis : first International Workshop, MOVI 2022, held in conjunction with MICCAI 2022, Singapore, September 18, 2022, Proceedings. MOVI (Workshop) (1st : 2022 : Singapore) · 2022Article
- Random Multi-Channel Image Synthesis for Multiplexed Immunofluorescence Imaging.Proceedings of machine learning research · 2021Article
- Inpainting Missing Tissue in Multiplexed Immunofluorescence Imaging.Proceedings of SPIE--the International Society for Optical EngineeringArticle
Corrections and comments
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Authors and funding
16 authors.
Funding
Abstract
The Gut Cell Atlas (GCA), an initiative funded by the Helmsley Charitable Trust, seeks to create a reference platform to understand the human gut, with a specific focus on Crohn's disease. Although a primary focus of the GCA is on focusing on single-cell profiling, we seek to provide a framework to integrate other analyses on multi-modality data such as electronic health record data, radiological images, and histology tissues/images. Herein, we use the research electronic data capture (REDCap) system as the central tool for a secure web application that supports protected health information (PHI) restricted access. Our innovations focus on addressing the challenges with tracking all specimens and biopsies, validating manual data entry at scale, and sharing organizational data across the group. We present a scalable, cross-platform barcode printing/record system that integrates with REDCap. The central informatics infrastructure to support our design is a tuple table to track longitudinal data entry and sample tracking. The current data collection (by December 2020) is illustrated with types and formats of the data that the system collects. We estimate that one terabyte is needed for data storage per patient study. Our proposed data sharing informatics system addresses the challenges with integrating physical sample tracking, large files, and manual data entry with REDCap.
Identifiers
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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.