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Amide proton transfer imaging for differentiation of benign and atypical meningiomas

European radiology, 2018-01, Vol.28 (1), p.331-339

2018

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Methodologic Guide for Evaluating Clinical Performance and Effect of Artificial Intelligence Technology for Medical Diagnosis and Prediction

Radiology, 2018-03, Vol.286 (3), p.800-809

2018

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Quality assessment of radiomics research in cardiac CT: a systematic review

European radiology, 2022-05, Vol.32 (5), p.3458-3468

2022

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Robust performance of deep learning for distinguishing glioblastoma from single brain metastasis using radiomic features: model development and validation

Scientific reports, 2020-07, Vol.10 (1), p.12110, Article 12110

2020

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Prevalence of abnormal cardiovascular magnetic resonance findings in recovered patients from COVID-19: a systematic review and meta-analysis

Journal of cardiovascular magnetic resonance, 2021-09, Vol.23 (1), p.100-100, Article 100

2021

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Changes in cancer detection and false-positive recall in mammography using artificial intelligence: a retrospective, multireader study

The Lancet. Digital health, 2020-03, Vol.2 (3), p.e138-e148

2020

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Statistical Methods for the Analysis of Inter-Reader Agreement Among Three or More Readers

Korean Journal of Radiology, 2024, 25(4), , pp.325-327

2024

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Restricted Mean Survival Time for Survival Analysis: A Quick Guide for Clinical Researchers

Korean Journal of Radiology, 2022, 23(5), , pp.495-499

2022

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Deep Convolutional Neural Network-based Software Improves Radiologist Detection of Malignant Lung Nodules on Chest Radiographs

Radiology, 2020-01, Vol.294 (1), p.199-209

2020

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Robust performance of deep learning for automatic detection and segmentation of brain metastases using three-dimensional black-blood and three-dimensional gradient echo imaging

European radiology, 2021-09, Vol.31 (9), p.6686-6695

2021

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Radiomics and machine learning may accurately predict the grade and histological subtype in meningiomas using conventional and diffusion tensor imaging

European radiology, 2019-08, Vol.29 (8), p.4068-4076

2019

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Application of artificial intelligence–based computer-assisted diagnosis on synthetic mammograms from breast tomosynthesis: comparison with digital mammograms

European radiology, 2021-09, Vol.31 (9), p.6929-6937

2021

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Patient-centered radiology reports with generative artificial intelligence: adding value to radiology reporting

Scientific reports, 2024-06, Vol.14 (1), p.13218-9

2024

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A radiomics-based model for predicting prognosis of locally advanced gastric cancer in the preoperative setting

Scientific reports, 2021-01, Vol.11 (1), p.1879-1879, Article 1879

2021

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Diffusion and perfusion MRI may predict EGFR amplification and the TERT promoter mutation status of IDH-wildtype lower-grade gliomas

European radiology, 2020-12, Vol.30 (12), p.6475-6484

2020

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Radiomics of US texture features in differential diagnosis between triple-negative breast cancer and fibroadenoma

Scientific reports, 2018-09, Vol.8 (1), p.13546-8, Article 13546

2018

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Radiomics machine learning study with a small sample size: Single random training-test set split may lead to unreliable results

PloS one, 2021-08, Vol.16 (8), p.e0256152-e0256152

2021

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Stability selection for LASSO with weights based on AUC

Scientific reports, 2023-03, Vol.13 (1), p.5207-5207, Article 5207

2023

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Prostate Cancer: PI-RADS Version 2 Helps Preoperatively Predict Clinically Significant Cancers

Radiology, 2016-07, Vol.280 (1), p.108-116

2016

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Three-dimensional radiomics of triple-negative breast cancer: Prediction of systemic recurrence

Scientific reports, 2020-02, Vol.10 (1), p.2976-2976, Article 2976

2020

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Amide proton transfer imaging might predict survival and IDH mutation status in high-grade glioma

European radiology, 2019-12, Vol.29 (12), p.6643-6652

2019

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Development of a new prognostic model to predict pneumonia outcome using artificial intelligence-based chest radiograph results

Scientific reports, 2024-06, Vol.14 (1), p.14415-9, Article 14415

2024

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Radiomics features of hippocampal regions in magnetic resonance imaging can differentiate medial temporal lobe epilepsy patients from healthy controls

Scientific reports, 2020-11, Vol.10 (1), p.19567-19567, Article 19567

2020

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Diffusion tensor and postcontrast T1-weighted imaging radiomics to differentiate the epidermal growth factor receptor mutation status of brain metastases from non-small cell lung cancer

Neuroradiology, 2021-03, Vol.63 (3), p.343-352

2021

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Implications of US radiomics signature for predicting malignancy in thyroid nodules with indeterminate cytology

European radiology, 2021-07, Vol.31 (7), p.5059-5067

2021

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Amide proton transfer imaging for differentiation of benign and atypical meningiomas

Methodologic Guide for Evaluating Clinical Performance and Effect of Artificial Intelligence Technology for Medical Diagnosis and Prediction

Quality assessment of radiomics research in cardiac CT: a systematic review

Robust performance of deep learning for distinguishing glioblastoma from single brain metastasis using radiomic features: model development and validation

Prevalence of abnormal cardiovascular magnetic resonance findings in recovered patients from COVID-19: a systematic review and meta-analysis

Changes in cancer detection and false-positive recall in mammography using artificial intelligence: a retrospective, multireader study

Statistical Methods for the Analysis of Inter-Reader Agreement Among Three or More Readers

Restricted Mean Survival Time for Survival Analysis: A Quick Guide for Clinical Researchers

Deep Convolutional Neural Network-based Software Improves Radiologist Detection of Malignant Lung Nodules on Chest Radiographs

Robust performance of deep learning for automatic detection and segmentation of brain metastases using three-dimensional black-blood and three-dimensional gradient echo imaging

Radiomics and machine learning may accurately predict the grade and histological subtype in meningiomas using conventional and diffusion tensor imaging

Application of artificial intelligence–based computer-assisted diagnosis on synthetic mammograms from breast tomosynthesis: comparison with digital mammograms

Patient-centered radiology reports with generative artificial intelligence: adding value to radiology reporting

A radiomics-based model for predicting prognosis of locally advanced gastric cancer in the preoperative setting

Diffusion and perfusion MRI may predict EGFR amplification and the TERT promoter mutation status of IDH-wildtype lower-grade gliomas

Radiomics of US texture features in differential diagnosis between triple-negative breast cancer and fibroadenoma

Radiomics machine learning study with a small sample size: Single random training-test set split may lead to unreliable results

Stability selection for LASSO with weights based on AUC

Prostate Cancer: PI-RADS Version 2 Helps Preoperatively Predict Clinically Significant Cancers

Three-dimensional radiomics of triple-negative breast cancer: Prediction of systemic recurrence

Amide proton transfer imaging might predict survival and IDH mutation status in high-grade glioma

Development of a new prognostic model to predict pneumonia outcome using artificial intelligence-based chest radiograph results

Radiomics features of hippocampal regions in magnetic resonance imaging can differentiate medial temporal lobe epilepsy patients from healthy controls

Diffusion tensor and postcontrast T1-weighted imaging radiomics to differentiate the epidermal growth factor receptor mutation status of brain metastases from non-small cell lung cancer

Implications of US radiomics signature for predicting malignancy in thyroid nodules with indeterminate cytology

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