ArticleIEEE transactions on medical imaging2021
Guest Editorial Annotation-Efficient Deep Learning: The Holy Grail of Medical Imaging.
Article in IEEE transactions on medical imaging, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 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
13 citing papers in PubMed.
- Clinician-accessible automated machine learning in oral healthcare: A systematic review.The Japanese dental science review · 2026Review
- Systematic review and meta-analysis of AI in lung cancer metastasis imaging for diagnosis and prognosis.NPJ digital medicine · 2026Article
- Unsupervised Variational-Autoencoder-Based Analysis of Morphological Representations in Magnetic-Nanoparticle-Treated Macrophages.Bioengineering (Basel, Switzerland) · 2026Article
- Article
- Time-to-Event Pretraining for 3D Medical Imaging.... International Conference on Learning Representations · 2025Article
- Applications, image analysis, and interpretation of computer vision in medical imaging.Frontiers in radiology · 2025Review
- SODU2-NET: a novel deep learning-based approach for salient object detection utilizing U-NET.PeerJ. Computer science · 2025Article
- Stepwise incremental pretraining for integrating discriminative, restorative, and adversarial learning.Medical image analysis · 2024Article
- Towards Foundation Models Learned from Anatomy in Medical Imaging via Self-supervision.Domain adaptation and representation transfer : 5th MICCAI Workshop, DART 2023, held in conjunction with MICCAI 2023, Vancouver, BC, Canada, October 12, 2023, Proceedings. Domain Adaptation and Representation Transfer (Workshop) (5th : ... · 2024Article
- Seeking an optimal approach for Computer-aided Diagnosis of Pulmonary Embolism.Medical image analysis · 2024Article
- Learning Anatomically Consistent Embedding for Chest Radiography.BMVC : proceedings of the British Machine Vision Conference. British Machine Vision Conference · 2023Article
- Discriminative, Restorative, and Adversarial Learning: Stepwise Incremental Pretraining.Domain adaptation and representation transfer : 4th MICCAI Workshop, DART 2022, held in conjunction with MICCAI 2022, Singapore, September 22, 2022, proceedings. Domain Adaptation and Representation Transfer (Workshop) (4th : 2022 : Sin... · 2022Article
- POPAR: Patch Order Prediction and Appearance Recovery for Self-supervised Medical Image Analysis.Domain adaptation and representation transfer : 4th MICCAI Workshop, DART 2022, held in conjunction with MICCAI 2022, Singapore, September 22, 2022, proceedings. Domain Adaptation and Representation Transfer (Workshop) (4th : 2022 : Sin... · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 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.