ArticleClinical radiology2020
Open access image repositories: high-quality data to enable machine learning research.
Article in Clinical radiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 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
24 citing papers in PubMed, 65 citations in OpenAlex.
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- Artificial intelligence in acupuncture: bridging traditional knowledge and precision integrative medicine.Frontiers in medicine · 2025Review
- High-resolution AI image dataset for diagnosing oral submucous fibrosis and squamous cell carcinoma.Scientific data · 2024Article
- Disparities in the Demographic Composition of The Cancer Imaging Archive.Radiology. Imaging cancer · 2024Article
- Weakly supervised segmentation models as explainable radiological classifiers for lung tumour detection on CT images.Insights into imaging · 2023Article
- Article
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- NeuroLINCS Proteomics: Defining human-derived iPSC proteomes and protein signatures of pluripotency.Scientific data · 2023Article
- Quantitative approaches in clinical reproductive endocrinology.Current opinion in endocrine and metabolic research · 2022Review
- A deep learning model for molecular label transfer that enables cancer cell identification from histopathology images.NPJ precision oncology · 2022Article
- Artificial intelligence in breast cancer imaging: risk stratification, lesion detection and classification, treatment planning and prognosis-a narrative review.Exploration of targeted anti-tumor therapy · 2022Review
- Deep Learning-Based Image Reconstruction for Different Medical Imaging Modalities.Computational and mathematical methods in medicine · 2022Review
- Radiation Oncology: Future Vision for Quality Assurance and Data Management in Clinical Trials and Translational Science.Frontiers in oncology · 2022Review
- Artificial intelligence and machine learning in cancer imaging.Communications medicine · 2022Review
- Technologic optimization of a virtual disease focused panel during the COVID pandemic and beyond.Abdominal radiology (New York) · 2021Article
- Artificial intelligence in child abuse imaging.Pediatric radiology · 2021Review
- COVID-19, AI enthusiasts, and toy datasets: radiology without radiologists.European radiology · 2021Article
- Development and operation of a digital platform for sharing pathology image data.BMC medical informatics and decision making · 2021Article
- Artificial intelligence and machine learning for medical imaging: A technology review.Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB) · 2021Review
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 at 5 institutions in 1 country.
Funding
Abstract
Originally motivated by the need for research reproducibility and data reuse, large-scale, open access information repositories have become key resources for training and testing of advanced machine learning applications in biomedical and clinical research. To be of value, such repositories must provide large, high-quality data sets, where quality is defined as minimising variance due to data collection protocols and data misrepresentations. Curation is the key to quality. We have constructed a large public access image repository, The Cancer Imaging Archive, dedicated to the promotion of open science to advance the global effort to diagnose and treat cancer. Drawing on this experience and our experience in applying machine learning techniques to the analysis of radiology and pathology image data, we will review the requirements placed on such information repositories by state-of-the-art machine learning applications and how these requirements can be met.
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.