ArticleExpert review of precision medicine and drug development2016
Radiomics: a new application from established techniques.
Article in Expert review of precision medicine and drug development, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 214 papers, 2 of them syntheses that pooled it.
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Who cites it
214 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Artificial Intelligence in Head and Neck Cancer: A Systematic Review of Systematic Reviews.Advances in therapy · 2023Pooled it
- The prognostic value of MRI-detected extramural vascular invasion (mrEMVI) for rectal cancer patients treated with neoadjuvant therapy: a meta-analysis.European radiology · 2021Pooled it
- MRCP-derived radiomics features associated with biliary dilation: a multi-step feature reduction, multivariable regression, and diagnostic classification study.Abdominal radiology (New York) · 2026Article
- From Symptom Control to Precision Supportive Oncology: Integrating Artificial Intelligence in Supportive Oncology for Gastrointestinal Cancers.Current oncology reports · 2026Review
- A Multi-Criterion Selection of Hybrid Features in Mammographic Imaging for Early Computer-Assisted Sensing and Detection of Breast Cancer.Sensors (Basel, Switzerland) · 2026Article
- Review
- Spinal Cord Radiomics-Driven Machine Learning Predicts Meaningful Clinical Improvement After Surgery for Degenerative Cervical Myelopathy: A Pilot Study.Journal of imaging informatics in medicine · 2026Article
- Artificial intelligence and radiomics in drug-induced interstitial lung disease.ERJ open research · 2026Review
- Machine-learning methods for epilepsy diagnosis and therapeutic prevention: advances, setbacks, and opportunities.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2026Review
- Pulmonary toxicity of immune checkpoint inhibitors.Breathe (Sheffield, England) · 2026Review
- Value of intratumoral and peritumoral radiomics based on DCE-MRI in predicting HER2-low and HER2-zero in breast cancer.BMC medical imaging · 2026Article
- Artificial Intelligence CT Texture Radiomics for Outcome Prediction After EVAR: A Narrative Review.Diagnostics (Basel, Switzerland) · 2026Review
- Manifold-based learning for high-throughput single-peanut phenotyping.NPJ systems biology and applications · 2026Article
- Radiomics for Detection and Differentiation of Intrahepatic Cholangiocarcinoma: A Systematic Review and Meta-Analysis.Cancers · 2026Review
- Precision Diagnosis in Cutaneous Head and Neck Squamous Cell Carcinoma.Biomedicines · 2026Review
- Artificial intelligence and machine learning-driven advancements in gastrointestinal cancer: Paving the way for precision medicine.World journal of gastroenterology · 2026Review
- Hippocampal subregional texture features associated with Alzheimer's disease severity and cognition.Brain communications · 2026Article
- Radiomics-based high-resolution CT analysis for differentiating primary tumor sources of pulmonary metastases.Frontiers in oncology · 2026Article
- Multiscale Brain Structural Network Reorganization in Diabetic Retinopathy Using Regional Radiomics Similarity Networks.Diabetes, metabolic syndrome and obesity : targets and therapy · 2026Article
- Radiomics-based mammographic abnormality identification via radiologist annotations.BJR artificial intelligence · 2026Article
154 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
The increasing use of biomarkers in cancer have led to the concept of personalized medicine for patients. Personalized medicine provides better diagnosis and treatment options available to clinicians. Radiological imaging techniques provide an opportunity to deliver unique data on different types of tissue. However, obtaining useful information from all radiological data is challenging in the era of "big data". Recent advances in computational power and the use of genomics have generated a new area of research termed Radiomics. Radiomics is defined as the high throughput extraction of quantitative imaging features or texture (radiomics) from imaging to decode tissue pathology and creating a high dimensional data set for feature extraction. Radiomic features provide information about the gray-scale patterns, inter-pixel relationships. In addition, shape and spectral properties can be extracted within the same regions of interest on radiological images. Moreover, these features can be further used to develop computational models using advanced machine learning algorithms that may serve as a tool for personalized diagnosis and treatment guidance.
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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.