ReviewFrontiers in oncology2020
The Era of Radiogenomics in Precision Medicine: An Emerging Approach to Support Diagnosis, Treatment Decisions, and Prognostication in Oncology.
Review in Frontiers in oncology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 85 papers, 6 of them syntheses that pooled it.
What it found
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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
85 citing papers in PubMed, 6 syntheses or guidelines pooled it.
- Radiogenomic profiling to determine BRCA alteration status-a systematic review and meta-analysis.The British journal of radiology · 2025Pooled it
- Pretreatment CT Texture Analysis for Predicting Survival Outcomes in Advanced Nonsmall Cell Lung Cancer Patients Receiving Immunotherapy: A Systematic Review and Meta-Analysis.Thoracic cancer · 2025Pooled it
- Association of radiomic features with genomic signatures in thyroid cancer: a systematic review.Journal of translational medicine · 2024Pooled it
- Role of radiomics as a predictor of disease recurrence in ovarian cancer: a systematic review.Abdominal radiology (New York) · 2024Pooled it
- Radiomics vs radiologist in prostate cancer. Results from a systematic review.World journal of urology · 2023Pooled it
- What Genetics Can Do for Oncological Imaging: A Systematic Review of the Genetic Validation Data Used in Radiomics Studies.International journal of molecular sciences · 2022Pooled it
- Radiogenomics for Glioblastoma Survival Prediction: Integrating Radiomics, Clinical, and Genomic Features Using Artificial Intelligence.Journal of imaging informatics in medicine · 2026Article
- Review
- From imaging to omics: deep learning is bridging MRI and liquid biopsy in bone tumor diagnosis.Journal of bone oncology · 2026Review
- IRDRM: Exploring Biological Traits and Clinical Significance in Breast Cancer Through Gene Pairs and Somatic Mutation Profiles.Interdisciplinary sciences, computational life sciences · 2026Article
- Health economics evaluation of artificial intelligence in the field of oncology: a scoping review.Health economics review · 2026Review
- AI-powered radiogenomics: imaging-driven diagnosis and discovery of cancer's molecular and cellular landscape.Molecular genetics and genomics : MGG · 2026Review
- Ionizing radiation: molecular mechanisms, biological effects, and therapeutic targets.Molecular biomedicine · 2026Review
- Fostering equity in precision health through diverse 3D facial data.Frontiers in medical technology · 2026Article
- Radiomics-based machine learning models for predicting genomic alterations in metastatic prostate cancer using PSMA PET imaging: a pilot study.EJNMMI reports · 2025Article
- Radiogenomics: A Machine Learning Augmentation to MRI-Based Glioma Profiling.Asian journal of neurosurgery · 2025Article
- Precision Oncology: Current Landscape, Emerging Trends, Challenges, and Future Perspectives.Cells · 2025Review
- Biomarkers in Stereotactic Ablative Radiotherapy: Current Evidence and Future Directions.International journal of molecular sciences · 2025Review
- Colorectal cancer liver metastases: A radiologic point of view.World journal of gastrointestinal oncology · 2025Article
- Machine Learning Model Integrating Computed Tomography Image-Derived Radiomics and Circulating miRNAs to Predict Residual Teratoma in Metastatic Nonseminoma Testicular Cancer.JCO clinical cancer informatics · 2025Article
25 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
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
With the rapid development of new technologies, including artificial intelligence and genome sequencing, radiogenomics has emerged as a state-of-the-art science in the field of individualized medicine. Radiogenomics combines a large volume of quantitative data extracted from medical images with individual genomic phenotypes and constructs a prediction model through deep learning to stratify patients, guide therapeutic strategies, and evaluate clinical outcomes. Recent studies of various types of tumors demonstrate the predictive value of radiogenomics. And some of the issues in the radiogenomic analysis and the solutions from prior works are presented. Although the workflow criteria and international agreed guidelines for statistical methods need to be confirmed, radiogenomics represents a repeatable and cost-effective approach for the detection of continuous changes and is a promising surrogate for invasive interventions. Therefore, radiogenomics could facilitate computer-aided diagnosis, treatment, and prediction of the prognosis in patients with tumors in the routine clinical setting. Here, we summarize the integrated process of radiogenomics and introduce the crucial strategies and statistical algorithms involved in current studies.
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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.