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Radiomic Machine-Learning Classifiers for Prognostic Biomarkers of Head and Neck Cancer

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Somatic Mutations Drive Distinct Imaging Phenotypes in Lung Cancer

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Textural features in pre-treatment [F18]-FDG-PET/CT are correlated with risk of local recurrence and disease-specific survival in early stage NSCLC patients receiving primary stereotactic radiation therapy

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Radiomics based targeted radiotherapy planning (Rad-TRaP): a computational framework for prostate cancer treatment planning with MRI

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The Role of Artificial Intelligence (AI) in Radiation Protection of Computed Tomography and Fluoroscopy: A Review

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ContraSurv: Enhancing Prognostic Assessment of Medical Images via Data-Efficient Weakly Supervised Contrastive Learning

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Radiogenomics Based on PET Imaging

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Enhanced childhood diseases treatment using computational models: Systematic review of intelligent experiments heading to precision medicine

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Three-dimensional iodine mapping quantified by dual-energy CT for predicting programmed death-ligand 1 expression in invasive pulmonary adenocarcinoma

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Role of Radiomics-based Multiomics Panel in the Microenvironment and Prognosis of Hepatocellular Carcinoma.

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Impact of neoadjuvant androgen deprivation therapy on magnetic resonance imaging features in prostate cancer before radiotherapy

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A Focus on the Synergy of Radiomics and RNA Sequencing in Breast Cancer

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The impact of radiomics in the management of soft tissue sarcoma

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Adapting training for medical physicists to match future trends in radiation oncology

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Making sense of radiomics: insights on human–AI collaboration in medical interaction from an observational user study

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Radiographic Image Radiomics Feature Reproducibility: A Preliminary Study on the Impact of Field Size

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Overlooked pitfalls in multi-class machine learning classification in radiation oncology and how to avoid them

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Wasserstein-based texture analysis in radiomic studies

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Robust machine learning challenge: An AIFM multicentric competition to spread knowledge, identify common pitfalls and recommend best practice

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The influence of artificial intelligence on the work of the medical physicist in radiotherapy practice: a short review

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Machine Learning based Prediction of Pain Response to Palliative Radiation Therapy - is there a Role for Planning CT-based Radiomics and Semantic Imaging Features?Preprint

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CEM radiomics for distinguishing lesion from background parenchymal enhancement in patients with invasive breast cancer

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Prognosis from Pixels: A Vendor-Protocol-Specific CT-Radiomics Model for Predicting Recurrence in Resected Lung Adenocarcinoma

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Preoperative contrast-enhanced CT-based radiomics signature for predicting hypoxia-inducible factor 1α expression in retroperitoneal sarcoma

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A comprehensive evaluation of MR-radiomics role in NAR score prediction in locally advanced rectal cancer

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Optimizing Rectal Cancer Patient Care: Dworak TRG Prediction via Bayesian Evolutionary Fourier-Domain Random Subspace Forest

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A Radiomics Model for the Differentiation of Intracranial Solitary Fibrous Tumor/Hemangiopericytoma and Meningioma Based on Multiparametric Magnetic Resonance Imaging

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Bridging the Gap Between Machine Learning and Medicine: A Critical Evaluation of the Dworak Regression Grade in Rectal Cancer

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Development of a graphic interface for the three-dimensional semiautomatic glioblastoma segmentation based on magnetic resonance images

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Radiomics Based Diagnosis with Medical Imaging: A Comprehensive Study

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Repurposing Routine Imaging for Cancer Biomarker Discovery Using Machine Learning

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Radiomics of Multi-modality Ultrasound in Rabbit VX2 Liver Tumors: Differentiating Residual Tumors from Hyperemic Rim After Ablation

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Optimal Mass Transport for Robust Texture AnalysisPreprint

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Supervised Image Classification Algorithm Using Representative Spatial Texture Features: Application to COVID-19 Diagnosis Using CT ImagesPreprint

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Ultrasound radiomics-based dynamic nomogram to predict histologic grade in soft tissue sarcoma: a multicenter cohort study

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Big data analytics and radiomics to discover diagnostics on different cancer types

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Extracting critical data from medical images based on machine learning

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Application and constraints of AI in radiomics and radiogenomics (R-n-R) studies of neuro-oncology

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Research Trends and Evolution in Radiogenomics (2005-2023): Bibliometric Analysis

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Integrating AI and Human Expertise: Exploring the Role of Radiomics in Multidisciplinary Tumor Boards

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Radiomics Approach for Cutaneous Melanoma Treatment Response Assessment in The Era of Precision Medicine

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Robust Texture Analysis via Optimal Mass Transport: Application to Medical Images Classification

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Generative models improve radiomics

Chen, J. (2023) · doi:10.26481/dis.20230703jc

CEM Radiomics for Distinguishing Benign vs Malignant Lesions in Patients with Invasive Breast Cancer or Benign Breast Lesions

Fields, J., Cen, S., Lei, X., Chang, M., Kinkar, K. K., Gujar, S. A., Lee, S., Hovanessian‐Larsen, L., Yamashita, M. W., Hwang, D., et al. (2024) · International Symposium on Medical Information Processing and Analysis (SIPAIM) · doi:10.1109/sipaim62974.2024.10783603

The impracticality of radiomics research in acute ischemic stroke: from the perspective of primary healthcare institutions

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Artificial neural network-augmented dosiomic integration for predicting distant recurrence in NSCLC patients treated with SBRT

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Additional file 2 of Value assessment of artificial intelligence in medical imaging: a scoping review

Fasterholdt, I., Naghavi‐Behzad, M., Rasmussen, B. S. B., Kjølhede, T., Skjøth, M. M., Hildebrandt, M. G., & Kidholm, K. (2022) · Figshare · doi:10.6084/m9.figshare.21443630

Additional file 1 of Value assessment of artificial intelligence in medical imaging: a scoping review

Fasterholdt, I., Naghavi‐Behzad, M., Rasmussen, B. S. B., Kjølhede, T., Skjøth, M. M., Hildebrandt, M. G., & Kidholm, K. (2022) · Figshare · doi:10.6084/m9.figshare.21443627

Identification of Glioma Phenotypic Subtypes From Multimodal MRI Data Using Hierarchical Multi‐Kernel Learning

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Réseaux antagonistes génératifs appliqués à l'imagerie médicale : adaptation de domaine pour réduire l'effet de centre dans le cadre d'études cliniques

Hognon, C. (2023) · doi:10.70675/f962a95azb578z4885zb9dez5d01e496284c

Radiomics and artificial intelligence: how medical physicists can help their translation into radiology, molecular imaging and radiation therapy routine clinical practice?

Bouchareb, Y., Khaniabadi, P. M., Al-Dhuhli, H., & Al-Kindi, F. (2021) · Physica Medica · doi:10.1016/s1120-1797(22)00087-4 · Cited by 3 · see citing works

Radiology and Radiomics: Towards Oncology Prediction with IA and Big Data

Ayres, A. S., Ferraciolli, S. F., Mota, A. L., Polsin, L. L. M., & Leite, C. D. C. (2022) · Integrated science · doi:10.1007/978-3-031-11199-0_12 · Cited by 2 · see citing works

“Radio-oncomics”

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Radiomics in radiation oncology—basics, methods, and limitations

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On the Fuzziness of Machine Learning, Neural Networks, and Artificial Intelligence in Radiation Oncology

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