ArticleBritish journal of haematology2022
Artificial intelligence recognition of cutaneous chronic graft-versus-host disease by a deep learning neural network.
Article in British journal of haematology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 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
13 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Toward Better Response Assessment of Cutaneous Chronic Graft-Versus-Host Disease: A Report from the National Institutes of Health Consensus Project Task Force.Transplantation and cellular therapy · 2026Guideline
- Erythema and hyperpigmentation delineation for cutaneous chronic graft-versus-host disease using hyperspectral reconstruction.Biomedical optics express · 2026Article
- Chronic graft-versus-host disease.Nature reviews. Disease primers · 2026Review
- Advanced Grafting Biomaterials and Technologies in Chronic Wound Care: Mechanisms, Clinical Outcomes, and Therapeutic Integration.Journal of functional biomaterials · 2026Review
- NIH Chronic Graft-Versus-Host Disease Consensus Conference 2025 Update.Transplantation and cellular therapy · 2025Review
- Mpox lesion counting with semantic and instance segmentation methods.Journal of medical imaging (Bellingham, Wash.) · 2025Article
- Improving U-Net Segmentation of Cutaneous Chronic Graft-Versus-Host Disease in Clinical Photographs with Semi-Supervised Training.Proceedings of SPIE--the International Society for Optical Engineering · 2025Article
- Modern-Era Challenges in the Clinical Management of Graft-Versus-Host Disease.Advances in experimental medicine and biology · 2025Review
- Cutaneous Chronic Graft-Versus-Host Disease: Clinical Manifestations, Diagnosis, Management, and Supportive Care.Transplantation and cellular therapy · 2024Review
- Crowdsourcing Skin Demarcations of Chronic Graft-Versus-Host Disease in Patient Photographs: Training Versus Performance Study.JMIR dermatology · 2023Article
- Predicting the severity of postoperative scars using artificial intelligence based on images and clinical data.Scientific reports · 2023Article
- Non-Expert Markings of Active Chronic Graft-Versus-Host Disease Photographs: Optimal Metrics of Training Effects.Journal of digital imaging · 2023Article
- Review
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
PubMed holds no abstract for this paper.
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.