ReviewNature reviews. Clinical oncology2017
Radiomics: the bridge between medical imaging and personalized medicine.
Review in Nature reviews. Clinical oncology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 5 registered trials, which are not on this map. Cited by 3,336 papers, 12 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.
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)
MR-based Models for Noninvasive Detection of Clinically Significant Portal Hypertension in Cirrhosis (CHESS1802)
Unravelling Tumour Biology In Ovarian Cancer With Precision Imaging
ATTRACT - ArTificial inTelligence-based RAdiogenomics in Colon Tumors
Use of Artificial Intelligence in Breast Cancer Screening: Impact of AI-Assisted Single Reading by One Radiologist on Screening Quality Indicators Compared to Standard Double Reading by Two Radiologists Without AI
Who cites it
3,336 citing papers in PubMed, 12 syntheses or guidelines pooled it.
- Application advances of habitat imaging based on CT or PET/CT: a systematic review.La Radiologia medica · 2026Pooled it
- Artificial intelligence in trigeminal neuralgia: trigeminal nerve segmentation and neurovascular conflict detection: a systematic review and meta-analysis.Neurosurgical review · 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
- 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
- Performance of Machine Learning Models Based on Medical Imaging in Predicting Pathological Grade of Clear Cell Renal Cell Carcinoma.Cancer medicine · 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
- MRI-Based Radiomics and Artificial Intelligence for Prediction of Recurrence and Prognostic Outcomes in Oral Tongue Squamous Cell Carcinoma: A Systematic Review with Functional Meta-Synthesis.Medical sciences (Basel, Switzerland) · 2026Pooled it
- Application Value of Radiomics-Based Machine Learning for Preoperative Risk Stratification of Bladder Cancer: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2026Pooled it
- A methodological framework for integrating generalisable deep learning and radiomics fusion model for early lung cancer detection across multi-centre imaging datasets.BMC medical informatics and decision making · 2026Pooled it
- Ultrasound-based predictive models for response to neoadjuvant chemotherapy in breast cancer: a systematic review and meta-analysis.BMC cancer · 2026Pooled it
- CT and MRI radiomics in cardiovascular risk prediction: a systematic review and meta-analysis by the EuSoMII Radiomics Auditing Group.European radiology · 2026Pooled it
- On the value of radiomics in addition to clinical measures in emotional conflict fMRI for predicting sertraline response in major depressive disorder.Scientific reports · 2026Trial
- Performance of magnetic-resonance imaging radiomics in prediction of response after neoadjuvant chemotherapy in head and neck squamous cell carcinoma: A systematic review and meta-analysis.European journal of radiology open · 2026Article
- 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
- Contrast-enhanced CT based radiomics for prediction of 3-year disease progression in NSCLC patients after anti-PD-1-targeted therapy.European journal of radiology open · 2026Article
- DCE-MRI kinetic heterogeneity facilitates the discrimination of benignity and malignancy of breast in combination with the DWI and morphological features.European journal of radiology open · 2026Article
- Moran's I-driven habitat radiomics: A biologically plausible and temporally robust approach for risk stratification of lung adenocarcinoma invasiveness.European journal of radiology open · 2026Article
- Hepatobiliary phase radiomics for identifying subclinical liver dysfunction in compensated chronic liver disease: development and external validation.Abdominal radiology (New York) · 2026Article
- MRCP-derived radiomics features associated with biliary dilation: a multi-step feature reduction, multivariable regression, and diagnostic classification study.Abdominal radiology (New York) · 2026Article
3,276 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
20 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Radiomics, the high-throughput mining of quantitative image features from standard-of-care medical imaging that enables data to be extracted and applied within clinical-decision support systems to improve diagnostic, prognostic, and predictive accuracy, is gaining importance in cancer research. Radiomic analysis exploits sophisticated image analysis tools and the rapid development and validation of medical imaging data that uses image-based signatures for precision diagnosis and treatment, providing a powerful tool in modern medicine. Herein, we describe the process of radiomics, its pitfalls, challenges, opportunities, and its capacity to improve clinical decision making, emphasizing the utility for patients with cancer. Currently, the field of radiomics lacks standardized evaluation of both the scientific integrity and the clinical relevance of the numerous published radiomics investigations resulting from the rapid growth of this area. Rigorous evaluation criteria and reporting guidelines need to be established in order for radiomics to mature as a discipline. Herein, we provide guidance for investigations to meet this urgent need in the field of radiomics.
Indexed as
Identifiers
28975929What 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.