ArticleScientific data2017
The public cancer radiology imaging collections of The Cancer Imaging Archive.
Article in Scientific data, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 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
58 citing papers in PubMed.
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- Interpretable ADC-based radiomics models for differentiating hepatocellular carcinoma and intrahepatic cholangiocarcinoma.Frontiers in oncology · 2026Article
- Resources and applications of public biomedical data.Frontiers in bioinformatics · 2026Review
- Machine learning in cancer imaging for enhanced precision in diagnosis and therapy.Discover computing · 2026Review
- BCMM: gated bidirectional cross-attention fusion of breast MRI and clinical features for predicting RCB response in the I-SPY1 cohort.Frontiers in artificial intelligence · 2026Article
- Sarcopenia-driven gene model as a clinically actionable prognostic signature for head and neck squamous cell carcinoma.Translational cancer research · 2025Article
- Integrated genetic and epigenetic analysis identifies that rs939408 affects non-smoking lung adenocarcinoma risk by modulating the DNA methylation of LRRC2.Cell death & disease · 2025Article
- Informatics at the Frontier of Cancer Research.Cancer research · 2025Review
- Ki-67 as a Predictor of Metastasis in Adrenocortical Carcinoma: Artificial Intelligence Insights from Retrospective Imaging Data.Journal of clinical medicine · 2025Article
- Intelligent health model for medical imaging to guide laymen using neural cellular automata.Scientific reports · 2025Article
- Prediction of radiosensitivity in non-small cell lung cancer based on computed tomography and tumor genomics: a multiple real world cohort study.Respiratory research · 2025Article
- AI-ready rectal cancer MR imaging: a workflow for tumor detection and segmentation.BMC medical imaging · 2025Article
- Under-representation for Female Pelvis Cancers in Commercial Auto-segmentation Solutions and Open-source Imaging Datasets.Clinical oncology (Royal College of Radiologists (Great Britain)) · 2025Article
- GastroHUN an Endoscopy Dataset of Complete Systematic Screening Protocol for the Stomach.Scientific data · 2025Article
- The Venus score for the assessment of the quality and trustworthiness of biomedical datasets.BioData mining · 2025Article
- Advancements in Cancer Care by Exploring Multimodality Imaging Techniques and their Applications.Current medical imaging · 2025Review
- Decoding Radiomics: A Step-by-Step Guide to Machine Learning Workflow in Hand-Crafted and Deep Learning Radiomics Studies.Diagnostics (Basel, Switzerland) · 2024Review
- A Cross Spatio-Temporal Pathology-based Lung Nodule Dataset.Scientific data · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
The Cancer Imaging Archive (TCIA) is the U.S. National Cancer Institute's repository for cancer imaging and related information. TCIA contains 30.9 million radiology images representing data collected from approximately 37,568 subjects. This data is organized into collections by tumor-type with many collections also including analytic results or clinical data. TCIA staff carefully de-identify and curate all incoming collections prior to making the information available via web browser or programmatic interfaces. Each published collection within TCIA is assigned a Digital Object Identifier that references the collection. Additionally, researchers who use TCIA data may publish the subset of information used in their analysis by requesting a TCIA generated Digital Object Identifier. This data descriptor is a review of a selected subset of existing publicly available TCIA collections. It outlines the curation and publication methods employed by TCIA and makes available 15 collections of cancer imaging data.
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.