ArticleNature machine intelligence2021
Radiological tumor classification across imaging modality and histology.
Article in Nature machine intelligence, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers, 3 of them syntheses that pooled it.
What it found
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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
53 citing papers in PubMed, 3 syntheses or guidelines pooled it, 90 citations in OpenAlex.
- Performance of Artificial Intelligence Models in Predicting Responsiveness of Hepatocellular Carcinoma to Transarterial Chemoembolization (TACE): A Systematic Review and Meta-Analysis.Journal of the American College of Radiology : JACR · 2026Pooled it
- Bibliometric insight into neoadjuvant immunotherapy in non-small cell lung cancer: trends, collaborations, and future avenues.Frontiers in immunology · 2025Pooled it
- Machine Learning Models for the Identification of Prognostic and Predictive Cancer Biomarkers: A Systematic Review.International journal of molecular sciences · 2023Pooled it
- Causal AI-based clinical and radiomic analysis for optimizing patient selection in combined immunotherapy and SABR in early-stage NSCLC: a secondary analysis of the phase II I-SABR trial.Journal for immunotherapy of cancer · 2025Trial
- Radiomics: Current Applications and Future Directions.MedComm · 2026Review
- The role of radiomics in predicting the response to neoadjuvant chemotherapy for breast cancer.Cancer biology & medicine · 2026Review
- Leveraging Large Language Models for Accurate AO Fracture Classification from CT Text Reports.Journal of imaging informatics in medicine · 2026Article
- Prediction of tumor-infiltrating lymphocytes through habitat radiomics and exploration of response mechanisms in neoadjuvant immunochemotherapy-treated lung cancer.Cancer immunology, immunotherapy : CII · 2026Article
- A Sensor-Oriented Multimodal Medical Data Acquisition and Modeling Framework for Tumor Grading and Treatment Response Analysis.Sensors (Basel, Switzerland) · 2026Article
- Radiogenomics predicts immune microenvironment heterogeneity and response to combination immunotherapy in hepatocellular carcinoma.Journal of translational medicine · 2026Article
- ADC-based radiomics for risk stratification in prostate cancer: a clinical decision support study.Frontiers in oncology · 2026Article
- Multimodal Fusion of 3D CT and Pathological Images for Gastric Cancer Recurrence Prediction.Cancer management and research · 2026Article
- Multiscale Pancancer Analysis Uncovers Intrinsic Imaging and Molecular Characteristics Prominent in Breast Cancer and Glioblastoma.British journal of cancer · 2026Article
- Minibeam radiation therapy remodels tumor microenvironment and suppresses HIF-1α/VEGFR axis to overcome radioresistance in triple-negative breast cancer.NPJ precision oncology · 2025Article
- Mining tumor and surrounding tissue information using artificial intelligence to predict responses to EGFR-targeted therapies and immunotherapy in lung cancer: a multicenter attribution analysis.La Radiologia medica · 2025Article
- Multidisciplinary, Clinical Assessment of Accelerated Deep-Learning MRI Protocols at 1.5 T and 3 T After Intracranial Tumor Surgery and Their Influence on Residual Tumor Perception.Diagnostics (Basel, Switzerland) · 2025Article
- Progress and challenges of artificial intelligence in lung cancer clinical translation.NPJ precision oncology · 2025Review
- Pan-cancer analysis shapes the understanding of cancer biology and medicine.Cancer communications (London, England) · 2025Review
- Leveraging large language models for accurate classification of liver lesions from MRI reports.Computational and structural biotechnology journal · 2025Article
- Multidisciplinary quantitative and qualitative assessment of IDH-mutant gliomas with full diagnostic deep learning image reconstruction.European journal of radiology open · 2024Article
Corrections and comments
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Authors and funding
16 authors at 5 institutions in 3 countries.
Funding
Abstract
Radiomics refers to the high-throughput extraction of quantitative features from radiological scans and is widely used to search for imaging biomarkers for prediction of clinical outcomes. Current radiomic signatures suffer from limited reproducibility and generalizability, because most features are dependent on imaging modality and tumor histology, making them sensitive to variations in scan protocol. Here, we propose novel radiological features that are specially designed to ensure compatibility across diverse tissues and imaging contrast. These features provide systematic characterization of tumor morphology and spatial heterogeneity. In an international multi-institution study of 1,682 patients, we discover and validate four unifying imaging subtypes across three malignancies and two major imaging modalities. These tumor subtypes demonstrate distinct molecular characteristics and prognoses after conventional therapies. In advanced lung cancer treated with immunotherapy, one subtype is associated with improved survival and increased tumor-infiltrating lymphocytes compared with the others. Deep learning enables automatic tumor segmentation and reproducible subtype identification, which can facilitate practical implementation. The unifying radiological tumor classification may inform prognosis and treatment response for precision medicine.
Identifiers
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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.