ArticleRadiology2016
Radiomics: Images Are More than Pictures, They Are Data.
Article in Radiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 12 registered trials, which are not on this map. Cited by 4,885 papers, 7 of them syntheses 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.
Development and Validation of a Radiomics Signature for Clinically Significant Portal Hypertension in Cirrhosis (CHESS1701): a Prospective Multicenter Study
Development of a Machine Learning-based Model for Preoperative Prediction of Microvascular Invasion in Hepatocellular Carcinoma
Radiomics-based Surrogate of Endoscopy (rEndosc) for Noninvasive Prediction of Esophageal Varices and Risk Stratification of Variceal Hemorrhage in Hepatitis B Virus-related Cirrhosis (CHESS1703)
Radiomics for Prediction of Lymph Node Metastasis in Gastric Cancer（RPLNM）(GIPMCS-1701)
MR-based Models for Noninvasive Detection of Clinically Significant Portal Hypertension in Cirrhosis (CHESS1802)
Artificial Intelligence to Help Non-Small Cell Lung Cancer Patients: Measure Lung Cancer Biology and Treatment Response Via Imaging
The New Challenge of Decoding Rectal Cancer Signatures By Non-Invasive Imaging: A Retrospective Radiomics Study
Use of PET/MR Radiomics to Evaluate the Clinical Phenotypes, Response Status of Neoadjuvant Chemotherapy and Long-term Prognosis of Breast Cancer: a Preliminary Study
The Clinical Trial 01 to Evaluate the Effectiveness of MRI-based Computer Aided Diagnosis Software (V1) for Glioma Segmentation, Gene Prediction and Tumor Grading
ATTRACT - ArTificial inTelligence-based RAdiogenomics in Colon Tumors
Precision Imaging for Early Detection and Targeted Treatment Monitoring in Pancreatic Cancer
Development of a Tumor and Peritumor Radiomics-based Model to Predict the High-risk Surgical Margin and Prognosis of T3 and T4 Non-Small Cell Lung Cancer
Who cites it
4,885 citing papers in PubMed, 7 syntheses or guidelines pooled it.
- Assessing the performance of deep learning and hand-crafted radiomics models using MRI and ultrasound in predicting axillary lymph node status in breast cancer: a systematic review and meta-analysis.European radiology · 2026Pooled it
- Radiomics-based prediction of pituitary adenoma consistency: a systematic review and meta-analysis.La Radiologia medica · 2026Pooled it
- PET-CT radiomics and artificial intelligence for predicting lymph node metastasis in cervical cancer: a systematic review and meta-analysis.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026Pooled it
- Artificial intelligence for the prediction of synchronous and metachronous liver metastasis in colorectal cancer patients: a systematic review and meta-analysis.Abdominal radiology (New York) · 2026Pooled it
- Radiomics for Prediction of Microsatellite Instability Status in Gastric Cancer: A Systematic Review and Meta-Analysis.Journal of gastrointestinal cancer · 2026Pooled it
- Radiomics for differentiating ruptured intracranial aneurysms: overview, methodological quality evaluation using METRICS and RQS, and feature transportability validation using independent multi-center dataset.European radiology · 2026Pooled it
- Prediction of PD-L1 expression in nonsmall cell lung cancer using artificial intelligence models based on radiomics: a systematic review and meta-analysis.European respiratory review : an official journal of the European Respiratory Society · 2026Pooled it
- Metabolic heterogeneity-based radiomic model predicts treatment outcomes of primary mediastinal B-cell lymphoma patients in the IELSG37 study.British journal of haematology · 2026Trial
- Minimal residual disease and relapse surveillance in osteosarcoma: an action-linked framework integrating liquid biopsy and imaging biomarkers.Journal of bone oncology · 2026Review
- Preoperative prediction of acute severe cholecystitis using an attentive interpretable tabular network (TabNet)-based radiomics model and a stacking ensemble: a two-center study.Annals of medicine · 2026Article
- Performance of MRI-based deep learning models in differentiation of triple negative breast cancer from other breast cancer subtypes: A systematic review and meta-analysis.European journal of radiology open · 2026Article
- Diagnostic performance and generalizability of a clinical-ultrasound radiomics model for predicting extrathyroidal extension in thyroid carcinoma: a retrospective study.Annals of medicine · 2026Article
- Intelligent immunotherapy: AI-driven optimization of CAR-T therapy in hematologic malignancies.iScience · 2026Review
- Hepatobiliary phase radiomics for identifying subclinical liver dysfunction in compensated chronic liver disease: development and external validation.Abdominal radiology (New York) · 2026Article
- Habitat-based radiomics-clinical analysis for early prediction of bladder cancer recurrence: a retrospective cohort study.Abdominal radiology (New York) · 2026Article
- Whole-axis versus odontoid process CBCT radiomics for forensic sex estimation: a retrospective paired-ROI model-development study.International journal of legal medicine · 2026Article
- Quality metrics of synthetic radiomics data do not predict improvement under simulated external validation: an ecological fallacy across 50 public datasets.European radiology · 2026Article
- Artificial intelligence in hepatocellular carcinoma: imaging-based subtyping and prediction of treatment response and prognosis.Abdominal radiology (New York) · 2026Review
- A multicenter study of automatic segmentation-based multimodal fusion integrating radiomics, deep learning, and clinical parameters for prostate cancer detection.Abdominal radiology (New York) · 2026Article
- Intratumoral habitat imaging for progression-free survival prediction of patients with high-risk, non-metastatic clear cell renal cell carcinoma.Abdominal radiology (New York) · 2026Article
4,825 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
In the past decade, the field of medical image analysis has grown exponentially, with an increased number of pattern recognition tools and an increase in data set sizes. These advances have facilitated the development of processes for high-throughput extraction of quantitative features that result in the conversion of images into mineable data and the subsequent analysis of these data for decision support; this practice is termed radiomics. This is in contrast to the traditional practice of treating medical images as pictures intended solely for visual interpretation. Radiomic data contain first-, second-, and higher-order statistics. These data are combined with other patient data and are mined with sophisticated bioinformatics tools to develop models that may potentially improve diagnostic, prognostic, and predictive accuracy. Because radiomics analyses are intended to be conducted with standard of care images, it is conceivable that conversion of digital images to mineable data will eventually become routine practice. This report describes the process of radiomics, its challenges, and its potential power to facilitate better clinical decision making, particularly in the care of patients with cancer.
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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.