Promises and challenges for the implementation of computational medical imaging (radiomics) in oncology

No abstract is available for this paper.

• Publication year

  2017

• Venue

  Annals of Oncology

• Publication date

  2017-06-01

• Fields of study

  Medicine, Computer Science, Engineering

• Identifiers
  DOI 10.1093/annonc/mdx034PMID 28168275
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

• Learning MRI-based classification models for MGMT methylation status prediction in glioblastoma

  2017cited by this paper
• Reproducibility of radiomics for deciphering tumor phenotype with imaging

  2016cited by this paper
• Automated 5-year mortality prediction using deep learning and radiomics features from chest computed tomography

  2016influential reference
• Computer-Aided Diagnosis with Deep Learning Architecture: Applications to Breast Lesions in US Images and Pulmonary Nodules in CT Scans

  2016cited by this paper
• Radiomics Analysis on FLT-PET/MRI for Characterization of Early Treatment Response in Renal Cell Carcinoma: A Proof-of-Concept Study

  2016cited by this paper
• MR Imaging Radiomics Signatures for Predicting the Risk of Breast Cancer Recurrence as Given by Research Versions of MammaPrint, Oncotype DX, and PAM50 Gene Assays.

  2016cited by this paper
• Quantitative MRI radiomics in the prediction of molecular classifications of breast cancer subtypes in the TCGA/TCIA data set

  2016cited by this paper
• Radiomics in glioblastoma: current status, challenges and potential opportunities

  2016cited by this paper
• Predicting Malignant Nodules from Screening CT Scans

  2016cited by this paper
• CT Features Associated with Epidermal Growth Factor Receptor Mutation Status in Patients with Lung Adenocarcinoma.

  2016cited by this paper
• Rectal Cancer: Assessment of Neoadjuvant Chemoradiation Outcome based on Radiomics of Multiparametric MRI

  2016cited by this paper
• Radiological Image Traits Predictive of Cancer Status in Pulmonary Nodules

  2016cited by this paper
• Prediction of malignant and benign of lung tumor using a quantitative radiomic method

  2016cited by this paper
• Radiomic Profiling of Glioblastoma: Identifying an Imaging Predictor of Patient Survival with Improved Performance over Established Clinical and Radiologic Risk Models.

  2016cited by this paper
• In Regard to Mattonen et al.

  2016cited by this paper
• Exploratory Study to Identify Radiomics Classifiers for Lung Cancer Histology

  2016cited by this paper
• Imaging biomarker roadmap for cancer studies

  2016cited by this paper
• Repeatability of Radiomic Features in Non-Small-Cell Lung Cancer [18F]FDG-PET/CT Studies: Impact of Reconstruction and Delineation

  2016cited by this paper
• Development and Validation of a Radiomics Nomogram for Preoperative Prediction of Lymph Node Metastasis in Colorectal Cancer.

  2016cited by this paper
• Mining textural knowledge in biological images: Applications, methods and trends

  2016cited by this paper
• The development and validation of a CT-based radiomics signature for the preoperative discrimination of stage I-II and stage III-IV colorectal cancer

  2016cited by this paper
• Impact of Reconstruction Algorithms on CT Radiomic Features of Pulmonary Tumors: Analysis of Intra- and Inter-Reader Variability and Inter-Reconstruction Algorithm Variability

  2016cited by this paper
• Identifying molecular genetic features and oncogenic pathways of clear cell renal cell carcinoma through the anatomical (PADUA) scoring system

  2016cited by this paper
• Deep learning based classification of breast tumors with shear-wave elastography.

  2016cited by this paper
• Prediction of malignant and benign of lung tumor using a quantitative radiomic method.

  2016cited by this paper
• Pulmonary Nodule Detection in CT Images: False Positive Reduction Using Multi-View Convolutional Networks

  2016cited by this paper
• Unsupervised Deep Learning Applied to Breast Density Segmentation and Mammographic Risk Scoring

  2016cited by this paper
• Defining a Radiomic Response Phenotype: A Pilot Study using targeted therapy in NSCLC

  2016cited by this paper
• Radiomics: Images Are More than Pictures, They Are Data

  2015cited by this paper
• Discovery Radiomics for Computed Tomography Cancer Detection

  2015influential reference
• External validation of a prognostic CT-based radiomic signature in oropharyngeal squamous cell carcinoma

  2015cited by this paper
• The effect of SUV discretization in quantitative FDG-PET Radiomics: the need for standardized methodology in tumor texture analysis

  2015cited by this paper
• Deciphering Genomic Underpinnings of Quantitative MRI-based Radiomic Phenotypes of Invasive Breast Carcinoma

  2015cited by this paper
• Radiomic feature clusters and Prognostic Signatures specific for Lung and Head & Neck cancer

  2015cited by this paper
• Machine Learning methods for Quantitative Radiomic Biomarkers

  2015cited by this paper
• Measuring Computed Tomography Scanner Variability of Radiomics Features

  2015cited by this paper
• Texture analysis on MR images helps predicting non-response to NAC in breast cancer

  2015cited by this paper
• CT-based radiomic signature predicts distant metastasis in lung adenocarcinoma.

  2015cited by this paper
• Non-Small Cell Lung Cancer Treated with Erlotinib: Heterogeneity of (18)F-FDG Uptake at PET-Association with Treatment Response and Prognosis.

  2015cited by this paper
• Pseudoprogression and Immune-Related Response in Solid Tumors.

  2015cited by this paper
• Is there a causal relationship between genetic changes and radiomics-based image features? An in vivo preclinical experiment with doxycycline inducible GADD34 tumor cells.

  2015cited by this paper
• Multi-scale Convolutional Neural Networks for Lung Nodule Classification

  2015influential reference
• Quantitative Computed Tomographic Descriptors Associate Tumor Shape Complexity and Intratumor Heterogeneity with Prognosis in Lung Adenocarcinoma

  2015cited by this paper
• Automated Texture Analysis for Prediction of Recurrence After Stereotactic Ablative Radiation Therapy for Lung Cancer

  2015cited by this paper
• Texture Analysis of Non–Contrast-Enhanced Computed Tomography for Assessing Angiogenesis and Survival of Soft Tissue Sarcoma

  2015cited by this paper
• Spatial Habitat Features Derived from Multiparametric Magnetic Resonance Imaging Data Are Associated with Molecular Subtype and 12-Month Survival Status in Glioblastoma Multiforme

  2015cited by this paper
• 18F-FDG PET-Derived Textural Indices Reflect Tissue-Specific Uptake Pattern in Non-Small Cell Lung Cancer

  2015influential reference
• PNAS Plus Significance Statements

  2015cited by this paper
• Textural Parameters of Tumor Heterogeneity in 18F-FDG PET/CT for Therapy Response Assessment and Prognosis in Patients with Locally Advanced Rectal Cancer

  2014cited by this paper
• PD-1 blockade induces responses by inhibiting adaptive immune resistance

  2014cited by this paper
• Tumor Texture Analysis in 18F-FDG PET: Relationships Between Texture Parameters, Histogram Indices, Standardized Uptake Values, Metabolic Volumes, and Total Lesion Glycolysis

  2014cited by this paper
• Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach

  2014influential reference
• Advanced Statistical Matrices for Texture Characterization: Application to Cell Classification

  2014cited by this paper
• The Effect of Small Tumor Volumes on Studies of Intratumoral Heterogeneity of Tracer Uptake

  2014cited by this paper
• Radiogenomic analysis of breast cancer: luminal B molecular subtype is associated with enhancement dynamics at MR imaging.

  2014cited by this paper
• Imaging Intratumor Heterogeneity: Role in Therapy Response, Resistance, and Clinical Outcome

  2014cited by this paper
• The Quantitative Imaging Network: NCI's Historical Perspective and Planned Goals.

  2014cited by this paper
• Test–Retest Reproducibility Analysis of Lung CT Image Features

  2014cited by this paper
• Robust Radiomics Feature Quantification Using Semiautomatic Volumetric Segmentation

  2014cited by this paper
• Joint learning and weighting of visual vocabulary for bag-of-feature based tissue classification

  2013influential reference
• Volumetric CT-based segmentation of NSCLC using 3D-Slicer

  2013cited by this paper
• Texture analysis in assessment and prediction of chemotherapy response in breast cancer

  2013cited by this paper
• Noninvasive Characterization of the Histopathologic Features of Pulmonary Nodules of the Lung Adenocarcinoma Spectrum using Computer-Aided Nodule Assessment and Risk Yield (CANARY)—A Pilot Study

  2013cited by this paper
• Influence of tumour micro-environment heterogeneity on therapeutic response

  2013cited by this paper
• Illuminating radiogenomic characteristics of glioblastoma multiforme through integration of MR imaging, messenger RNA expression, and DNA copy number variation.

  2013cited by this paper
• Pitfalls and limitations in translation from biomarker discovery to clinical utility in predictive and personalised medicine

  2013cited by this paper
• Non-small cell lung cancer: histopathologic correlates for texture parameters at CT.

  2013cited by this paper
• The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository

  2013cited by this paper
• Impact of Bioinformatic Procedures in the Development and Translation of High-Throughput Molecular Classifiers in Oncology

  2013cited by this paper
• Radiomics: the process and the challenges.

  2012cited by this paper
• Reporting Recommendations for Tumor Marker Prognostic Studies (REMARK): Explanation and Elaboration

  2012cited by this paper
• Radiomics: extracting more information from medical images using advanced feature analysis.

  2012cited by this paper
• Survival Analysis of Patients with High-Grade Gliomas Based on Data Mining of Imaging Variables

  2012cited by this paper
• A semiautomatic CT-based ensemble segmentation of lung tumors: comparison with oncologists' delineations and with the surgical specimen.

  2012cited by this paper
• Non-small cell lung cancer: identifying prognostic imaging biomarkers by leveraging public gene expression microarray data--methods and preliminary results.

  2012cited by this paper
• The hallmarks of cancer

  2012cited by this paper
• Reporting recommendations for tumor marker prognostic studies (REMARK): explanation and elaboration

  2012cited by this paper
• Reduced Lung-Cancer Mortality with Low-Dose Computed Tomographic Screening

  2012cited by this paper
• Investigating machine learning techniques for MRI-based classification of brain neoplasms

  2011cited by this paper
• Hallmarks of cancer: the next generation.

  2011cited by this paper
• Reduced lung-cancer mortality with low-dose computed tomographic screening.

  2011cited by this paper
• Molecular imaging-based dose painting: a novel paradigm for radiation therapy prescription.

  2011cited by this paper
• Probabilistic lung nodule classification with belief decision trees

  2011cited by this paper
• Assessment of response to tyrosine kinase inhibitors in metastatic renal cell cancer: CT texture as a predictive biomarker.

  2011cited by this paper
• Radiogenomic Mapping of Edema/Cellular Invasion MRI-Phenotypes in Glioblastoma Multiforme

  2011cited by this paper
• Variability of textural features in FDG PET images due to different acquisition modes and reconstruction parameters

  2010cited by this paper
• The Biomarkers Consortium: Practice and Pitfalls of Open‐Source Precompetitive Collaboration

  2010cited by this paper
• Computerized Image-Based Detection and Grading of Lymphocytic Infiltration in HER2+ Breast Cancer Histopathology

  2010cited by this paper
• Differential diagnosis and management of focal ground-glass opacities

  2010cited by this paper
• Texture analysis of non-small cell lung cancer on unenhanced computed tomography: initial evidence for a relationship with tumour glucose metabolism and stage

  2010cited by this paper
• Exporting Contours to DICOM-RT Structure Set

  2009cited by this paper
• Texture analysis in non-contrast enhanced CT: impact of malignancy on texture in apparently disease-free areas of the liver.

  2009cited by this paper
• Classification of brain tumor type and grade using MRI texture and shape in a machine learning scheme

  2009cited by this paper
• Exploring feature-based approaches in PET images for predicting cancer treatment outcomes

  2009cited by this paper
• Differential diagnosis and management of focal ground-glass opacities

  2009cited by this paper
• The Reference Image Database to Evaluate Response to Therapy in Lung Cancer (RIDER) Project: A Resource for the Development of Change‐Analysis Software

  2008cited by this paper
• The properties of high-dimensional data spaces: implications for exploring gene and protein expression data

  2008cited by this paper
• Identification of noninvasive imaging surrogates for brain tumor gene-expression modules

  2008cited by this paper
• Decoding global gene expression programs in liver cancer by noninvasive imaging

  2007cited by this paper
• STEP: SPATIAL-TEMPORAL ENHANCEMENT PATTERN, FOR MR-BASED BREAST TUMOR DIAGNOSIS

  2007cited by this paper

• Research Progress on the Application of Radiomics and Deep Learning in Liver Fibrosis.

  2026cites this paper
• A novel multimodal combining radiomics and tumor–stroma ratio (TSR) improves diagnosis of gastric cancer peritoneal metastasis

  2026cites this paper
• Image Quality Standardization in Radiomics: A Systematic Review of Artifacts, Variability, and Feature Stability

  2026cites this paper
• Single and multi-site CT-based radiogenomics analysis of metastatic lung adenocarcinoma and correlations with outcome.

  2026cites this paper
• Radiomics from Routine CT and PET/CT Imaging in Laryngeal Squamous Cell Carcinoma: A Systematic Review with Radiomics Quality Score Assessment

  2026cites this paper
• Beyond handcrafted radiomics in oncologic imaging: Innovations in deep, explainable, multi-site and multi-omics radiomics approaches.

  2026cites this paper
• TabPFN-driven ternary classification of stage IA lung adenocarcinoma subtypes using AI-derived histogram features a retrospective multicenter cohort study.

  2026cites this paper
• UAM: A Unified Attention-Mamba Backbone of Multimodal Framework for Tumor Cell Classification

  2025cites this paper
• Radiomic Analysis of Contrast‐Enhanced CT Predicts Recompensation in Hepatitis B‐Related Decompensated Cirrhosis

  2025cites this paper
• Dual-modal ultrasound-based deep learning radiomics for differentiation of benign and malignant breast lesions

  2025cites this paper
• Externally validated and clinically useful machine learning algorithms to support patient-related decision-making in oncology: a scoping review

  2025cites this paper
• Multimodal CT radiomics predicts PD-1 inhibitor efficacy in advanced gastric cancer: a two-center validation study

  2025cites this paper
• Clinical MRI-radiomics model based on support vector machine to predict the efficacy of first transarterial chemoembolization for unresectable intrahepatic cholangiocarcinoma.

  2025cites this paper
• PET-CT radiomics for immunotherapy response.

  2025cites this paper
• From texture analysis to artificial intelligence: global research landscape and evolutionary trajectory of radiomics in hepatocellular carcinoma

  2025cites this paper
• Sub-regional radiomics combining multichannel 2-dimensional or 3-dimensional deep learning for predicting neoadjuvant chemo-immunotherapy response in esophageal squamous cell carcinoma: a multicenter study

  2025cites this paper
• Enhanced Brain Cancer Detection Using a Radiomics-Informed Hybrid Autoencoder and GBM Model

  2025cites this paper
• Integrating Radiogenomics and Machine Learning in Musculoskeletal Oncology Care

  2025cites this paper
• CT-based radiomics analysis for predicting EGFR and ALK mutational status in non‑small cell lung cancer

  2025cites this paper
• Deep adaptive learning predicts and diagnoses CSVD-related cognitive decline using radiomics from T2-FLAIR: a multi-centre study

  2025cites this paper
• PET-based radiomic analysis in multicentre lung cancer study and impact of feature domain harmonization

  2025cites this paper
• Ultrasound radiomics-based dynamic nomogram to predict histologic grade in soft tissue sarcoma: a multi-center cohort study.

  2025cites this paper
• Clinical value of the nomogram model based on endoscopic ultrasonography radiomics and clinical indicators in identifying benign and malignant lesions of the pancreas

  2025cites this paper
• Deep Learning and Radiomics for Gastric Cancer Lymph Node Metastasis: Automated Segmentation and Multi-Machine Learning Study from Two Centers

  2025cites this paper
• MRI‐based radiomics models for early predicting pathological response to neoadjuvant chemotherapy in triple‐negative breast cancer: A systematic review and meta‐analysis

  2025influential citation
• Quantitative MR Imaging of the Breast

  2025cites this paper
• MRI-based radiomics for differention of aquaporin 4-immunoglobulin G-positive neuromyelitis optic spectrum disorder and anti myelin oligodendrocyte glycoprotein immunoglobulin G-associated disorder.

  2025cites this paper
• Integrating Deep Feature Extraction and MRI Radiomics for Survival Prediction in Breast Cancer After Neoadjuvant Chemotherapy.

  2025cites this paper
• Exploring the Role of CT-Based Delta-Radiomics in Unresectable Vulvar Cancer

  2025cites this paper
• Deciphering the biological underpinnings behind prognostic MRI-based imaging signatures in breast cancer: a systematic review

  2025cites this paper
• Artificial intelligence-based automated breast ultrasound radiomics for breast tumor diagnosis and treatment: a narrative review

  2025cites this paper
• Foundation model embeddings for quantitative tumor imaging biomarkers

  2025cites this paper
• Automatic Segmentation and Molecular Subtype Classification of Breast Cancer Using an MRI-based Deep Learning Framework.

  2025cites this paper
• Enhancing survival predictions in lung cancer with cystic airspaces: a multimodal approach combining clinical and radiomic features

  2025cites this paper
• Predicting prostate cancer radiotherapy complications: An integrated approach using radiomics, dosiomics, and machine learning

  2025cites this paper
• The Evolving Landscape of Radiomics in Gliomas: Insights into Diagnosis, Prognosis, and Research Trends

  2025cites this paper
• Breast Cancer Risk Prediction with Radiomic Tissue Characterization on Mammograms Takes Shape.

  2025cites this paper
• Non-invasive prediction of DCE-MRI radiomics model on CCR5 in breast cancer based on a machine learning algorithm

  2025cites this paper
• A radiomics-based model for predicting lymph nodes metastasis of pancreatic ductal adenocarcinoma: a multicenter study

  2025cites this paper
• Prediction Crohn's Disease Activity Using Computed Tomography Enterography-Based Radiomics and Serum Markers.

  2025cites this paper
• Exploring Strategies for Personalized Radiation Therapy Part I Unlocking Response-Related Tumor Subregions with Class Activation Mapping

  2025cites this paper
• Computed tomography-based radiomics prediction model for differentiating invasive pulmonary aspergillosis and Pneumocystis jirovecii pneumonia

  2025cites this paper
• Ensuring Reproducibility and Deploying Models with the Image2Radiomics Framework: An Evaluation of Image Processing on PanNET Model Performance

  2025cites this paper
• A prognostic model integrating radiomics and deep learning based on CT for survival prediction in laryngeal squamous cell carcinoma

  2025cites this paper
• An Interpretable Radiomics Model Integrating Ultrasound and Clinical Features for Multiclass Classification of Axillary Lymph Nodes.

  2025cites this paper
• Preoperative prediction of lymph node metastasis in adenocarcinoma of esophagogastric junction using CT texture analysis combined with machine learning

  2025cites this paper
• Effect of magnetic field strength and segmentation variability on the reproducibility and repeatability of radiomic texture features in cardiovascular magnetic resonance parametric mapping

  2025cites this paper
• Advancing cancer diagnosis and treatment: integrating image analysis and AI algorithms for enhanced clinical practice

  2025cites this paper
• Deep learning and radiomics for gastric cancer serosal invasion: automated segmentation and multi-machine learning from two centers

  2025cites this paper
• Radiomic analysis of patient and interorgan heterogeneity in response to immunotherapies and BRAF-targeted therapy in metastatic melanoma

  2025cites this paper
• Diagnostic Accuracy of Deep Learning for Predicting Lymph Node Metastasis Based on Computed Tomography in Gastric Cancer: A Systematic Review and Meta-analysis

  2025cites this paper
• Predicting outcomes in head and neck cancer using CT images via transfer learning

  2025cites this paper
• Radiomics for predicting sensitivity to neoadjuvant chemotherapy in osteosarcoma: current status and advances

  2025cites this paper
• Deep Subspace Reconstruction-Driven Adaptive Canonical Correlation Analysis Model for Identifying Imaging Genetics Associations in Sarcoma

  2025cites this paper
• Radiomics analysis of dual-layer detector spectral CT-derived iodine maps for predicting Ki-67 PI in pancreatic ductal adenocarcinoma

  2025cites this paper
• Prediction of sandstone freeze-thaw damage in the Changdu of the Qinghai-Tibet plateau based on CT radiomics method

  2025cites this paper
• Predicting tumor micronecrosis in hepatocellular carcinoma using pretreatment contrast-enhanced CT radiomics model: a multi-center study

  2025cites this paper
• Predictive performance of MRI and CT radiomics in predicting the response to induction chemotherapy in nasopharyngeal carcinoma: a network meta-analysis

  2025cites this paper
• Tumour habitat-based radiomics analysis enhances the ability to predict prostate cancer aggressiveness with biparametric MRI-derived features

  2025cites this paper
• A study on the value of ultrasound strain elastography-based radiomics nomogram in the differential diagnosis of breast masses

  2025cites this paper
• CBCT radiomics features combine machine learning to diagnose cystic lesions in the jaw.

  2025cites this paper
• MRI radiomics model using T2-weighted imaging sequences to differentiate small hepatic metastases and hemangiomas

  2025cites this paper
• Magnetic Resonance Imaging Radiomics-Based Model for Prediction of Lymph Node Metastasis in Cervical Cancer

  2025cites this paper
• The application of radiomics in cancer imaging with a focus on lung cancer, renal cell carcinoma, gastrointestinal cancer, and head and neck cancer: A systematic review.

  2025cites this paper
• Incorporating radiomic MRI models for presurgical response assessment in patients with early breast cancer undergoing neoadjuvant systemic therapy: collaborative insights from breast oncologists and radiologists.

  2025cites this paper
• Survival prediction with radiomics for patients with IDH mutated lower-grade glioma

  2025cites this paper
• Combining serum biomarkers and MRI radiomics to predict treatment outcome after thermal ablation in hepatocellular carcinoma.

  2025cites this paper
• A CNN–transformer fusion network for predicting high‐grade patterns in stage IA invasive lung adenocarcinoma

  2025cites this paper
• Patch-Based Texture Feature Extraction Towards Improved Clinical Task Performance

  2025cites this paper
• Heterogeneity of Lung Cancer: The Histopathological Diversity and Tumour Classification in the Artificial Intelligence Era

  2025cites this paper
• Survival Prediction of Esophageal Cancer Using 3D CT Imaging: A Context-Aware Approach With Non-Local Feature Aggregation and Graph-Based Spatial Interaction

  2025cites this paper
• Differentiation of Glioblastoma and Solitary Brain Metastasis Using Brain-Tumor Interface Radiomics Features Based on MR Images: A Multicenter Study.

  2025cites this paper
• Multicollinearity and redundancy of the PET radiomic feature set

  2025cites this paper
• The Many Faces of Intestinal Tumors in Adults, Including the Primary Role of CT Imaging in Emergencies and the Important Role of Cross-Sectional Imaging: A Pictorial Review

  2025influential citation
• Radiomics-based machine learning in prediction of response to neoadjuvant chemotherapy in osteosarcoma: A systematic review and meta-analysis.

  2025cites this paper
• Evaluating feature extraction reproducibility across image biomarker standardization initiative‐compliant radiomics platforms using a digital phantom

  2025cites this paper
• Prediction of KRAS gene mutations in colorectal cancer using a CT-based radiomic model

  2025cites this paper
• Deep learning models based on multiparametric magnetic resonance imaging and clinical parameters for identifying synchronous liver metastases from rectal cancer

  2025cites this paper
• Artificial Intelligence in Predicting Efficacy and Toxicity of Immunotherapy: Applications, Challenges, and Future Directions.

  2025cites this paper
• Three-dimensional multimodal imaging for predicting early recurrence of hepatocellular carcinoma after surgical resection.

  2025cites this paper
• Consensus clustering based on CT radiomics has potential for risk stratification of patients with clinical T1 stage lung adenocarcinoma

  2025cites this paper
• Developments in MRI radiomics research for vascular cognitive impairment

  2025cites this paper
• Current Applications and Development of Radiomics in Osteoporosis: A Narrative Review

  2025cites this paper
• Exploring Strategies for Personalized Radiation Therapy Part II Predicting Tumor Drift Patterns with Diffusion Models

  2025cites this paper
• Accurate Paediatric Brain Tumour Classification Through Improved Quantitative Analysis of 1H MR Imaging and Spectroscopy

  2025cites this paper
• Radiomics-based Machine Learning for Predicting Response to Immune Checkpoint Inhibitors in Hepatocellular Carcinoma: A Systematic Review and Meta-analysis.

  2025cites this paper
• Use of Radiomics in Characterizing Tumor Hypoxia

  2025cites this paper
• Immunophenotype-guided interpretable radiomics model for predicting neoadjuvant anti-PD-1 response in stage III–IV d-MMR/MSI-H colorectal cancer

  2025cites this paper
• Radiomics-based machine-learning method to predict extrahepatic metastasis in hepatocellular carcinoma after hepatectomy: a multicenter study

  2025cites this paper
• Computed tomography radiomics to predict microsatellite instability status and immunotherapy response in gastric cancer

  2025cites this paper
• Predicting EGFR mutation status in non-small cell lung cancer patients with brain metastases based on MRI radiomics: A systematic review and meta-analysis.

  2025cites this paper
• Overview of Multimodal Radiomics and Deep Learning in the Prediction of Axillary Lymph Node Status in Breast Cancer.

  2025cites this paper
• Construction and Value Analysis of a Prognostic Assessment Model Based on Radiomics and Genetic Data for Colorectal Cancer.

  2025cites this paper
• Artificial intelligence and radiomics biomarkers for treatment response prediction in advanced HER2-negative breast cancer

  2025cites this paper
• Pre-Treatment and Pre-Brachytherapy MRI first-order Radiomic Features by a Commercial software as survival predictors in radiotherapy for cervical cancer Objectives

  2025cites this paper
• Radiogenomics and machine learning predict oncogenic signaling pathways in glioblastoma

  2025cites this paper
• Stability of radiomic features in magnetic resonance imaging of the female pelvis: A multicentre phantom study.

  2025cites this paper
• Radiomics for osteoporosis detection – current opportunities and prospects: a literature review

  2025cites this paper
• A clinical-radiomics nomogram to predict early neurological deterioration in patients with stroke undergoing intravenous thrombolysis

  2025cites this paper
• Novel biomarkers for guiding treatment for prostate cancer.

  2025cites this paper