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Towards clinical application of image mining: a systematic review on artificial intelligence and radiomics

European journal of nuclear medicine and molecular imaging, 2019-12, Vol.46 (13), p.2656-2672

2019

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FDG-PET/CT findings highly suspicious for COVID-19 in an Italian case series of asymptomatic patients

European journal of nuclear medicine and molecular imaging, 2020-07, Vol.47 (7), p.1649-1656

2020

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State-of-the-art of FAPI-PET imaging: a systematic review and meta-analysis

European journal of nuclear medicine and molecular imaging, 2021-12, Vol.48 (13), p.4396-4414

2021

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Texture analysis and machine learning to characterize suspected thyroid nodules and differentiated thyroid cancer: Where do we stand?

European journal of radiology, 2018-02, Vol.99, p.1-8

2018

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Prediction of disease-free survival by the PET/CT radiomic signature in non-small cell lung cancer patients undergoing surgery

European journal of nuclear medicine and molecular imaging, 2018-02, Vol.45 (2), p.207-217

2018

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Ability of FDG PET and CT radiomics features to differentiate between primary and metastatic lung lesions

European journal of nuclear medicine and molecular imaging, 2018-09, Vol.45 (10), p.1649-1660

2018

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Climbing the steps of the evidence-based medicine pyramid: highlights from Annals of Nuclear Medicine 2019

European journal of nuclear medicine and molecular imaging, 2021-05, Vol.48 (5), p.1293-1301

2021

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PET/CT radiomics in breast cancer: promising tool for prediction of pathological response to neoadjuvant chemotherapy

European journal of nuclear medicine and molecular imaging, 2019-07, Vol.46 (7), p.1468-1477

2019

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Radiomics and gene expression profile to characterise the disease and predict outcome in patients with lung cancer

European journal of nuclear medicine and molecular imaging, 2021-10, Vol.48 (11), p.3643-3655

2021

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Computed tomography (CT)-derived radiomic features differentiate prevascular mediastinum masses as thymic neoplasms versus lymphomas

Radiologia medica, 2020-10, Vol.125 (10), p.951-960

2020

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Distributed learning: a reliable privacy-preserving strategy to change multicenter collaborations using AI

European journal of nuclear medicine and molecular imaging, 2021-11, Vol.48 (12), p.3791-3804

2021

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Dual adversarial deconfounding autoencoder for joint batch-effects removal from multi-center and multi-scanner radiomics data

Scientific reports, 2023-11, Vol.13 (1), p.18857-18857, Article 18857

2023

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Increased incidence of interstitial pneumonia detected on [18F]-FDG-PET/CT in asymptomatic cancer patients during COVID-19 pandemic in Lombardy: a casualty or COVID-19 infection?

European journal of nuclear medicine and molecular imaging, 2021-03, Vol.48 (3), p.777-785

2021

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Imaging-Based Prediction of Molecular Therapy Targets in NSCLC by Radiogenomics and AI Approaches: A Systematic Review

Diagnostics (Basel), 2020-05, Vol.10 (6), p.359

2020

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Radiomics based analysis to predict local control and survival in hepatocellular carcinoma patients treated with volumetric modulated arc therapy

BMC cancer, 2017-12, Vol.17 (1), p.829-829, Article 829

2017

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CT, [18F]FDG-PET/CT and clinical findings before and during early Covid-19 onset in a patient affected by vascular tumour

European journal of nuclear medicine and molecular imaging, 2020-07, Vol.47 (7), p.1769-1770

2020

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[18F]FDG PET/CT features for the molecular characterization of primary breast tumors

European journal of nuclear medicine and molecular imaging, 2017-11, Vol.44 (12), p.1945-1954

2017

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Computed tomography based radiomic signature as predictive of survival and local control after stereotactic body radiation therapy in pancreatic carcinoma

PloS one, 2019-01, Vol.14 (1), p.e0210758-e0210758

2019

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The five “W”s and “How” of Targeted Alpha Therapy: Why? Who? What? Where? When? and How?

Atti della Accademia nazionale dei Lincei. Rendiconti Lincei. Scienze fisiche e naturali, 2020-06, Vol.31 (2), p.231-247

2020

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Author Correction: Application of FLIC model to predict adverse events onset in neuroendocrine tumors treated with PRRT

Scientific reports, 2023-01, Vol.13 (1), p.1759-1759, Article 1759

2023

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The “3M” Approach to Cardiovascular Infections: Multimodality, Multitracers, and Multidisciplinary

Seminars in nuclear medicine, 2018-05, Vol.48 (3), p.199-224

2018

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The Development of an Intelligent Agent to Detect and Non-Invasively Characterize Lung Lesions on CT Scans: Ready for the "Real World"?

Cancers, 2023-01, Vol.15 (2), p.357

2023

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Deep learning in Nuclear Medicine—focus on CNN-based approaches for PET/CT and PET/MR: where do we stand?

Clinical and translational imaging : reviews in nuclear medicine and molecular imaging, 2021-02, Vol.9 (1), p.37-55

2021

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PSMA expression level predicts differentiated thyroid cancer aggressiveness and patient outcome

EJNMMI research, 2019-10, Vol.9 (1), p.1-13, Article 93

2019

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Image Embeddings Extracted from CNNs Outperform Other Transfer Learning Approaches in Classification of Chest Radiographs

Diagnostics (Basel), 2022-08, Vol.12 (9), p.2084

2022

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Towards clinical application of image mining: a systematic review on artificial intelligence and radiomics

FDG-PET/CT findings highly suspicious for COVID-19 in an Italian case series of asymptomatic patients

State-of-the-art of FAPI-PET imaging: a systematic review and meta-analysis

Texture analysis and machine learning to characterize suspected thyroid nodules and differentiated thyroid cancer: Where do we stand?

Prediction of disease-free survival by the PET/CT radiomic signature in non-small cell lung cancer patients undergoing surgery

Ability of FDG PET and CT radiomics features to differentiate between primary and metastatic lung lesions

Climbing the steps of the evidence-based medicine pyramid: highlights from Annals of Nuclear Medicine 2019

PET/CT radiomics in breast cancer: promising tool for prediction of pathological response to neoadjuvant chemotherapy

Radiomics and gene expression profile to characterise the disease and predict outcome in patients with lung cancer

Computed tomography (CT)-derived radiomic features differentiate prevascular mediastinum masses as thymic neoplasms versus lymphomas

Distributed learning: a reliable privacy-preserving strategy to change multicenter collaborations using AI

Dual adversarial deconfounding autoencoder for joint batch-effects removal from multi-center and multi-scanner radiomics data

Increased incidence of interstitial pneumonia detected on [18F]-FDG-PET/CT in asymptomatic cancer patients during COVID-19 pandemic in Lombardy: a casualty or COVID-19 infection?

Imaging-Based Prediction of Molecular Therapy Targets in NSCLC by Radiogenomics and AI Approaches: A Systematic Review

Radiomics based analysis to predict local control and survival in hepatocellular carcinoma patients treated with volumetric modulated arc therapy

CT, [18F]FDG-PET/CT and clinical findings before and during early Covid-19 onset in a patient affected by vascular tumour

[18F]FDG PET/CT features for the molecular characterization of primary breast tumors

Computed tomography based radiomic signature as predictive of survival and local control after stereotactic body radiation therapy in pancreatic carcinoma

The five “W”s and “How” of Targeted Alpha Therapy: Why? Who? What? Where? When? and How?

Author Correction: Application of FLIC model to predict adverse events onset in neuroendocrine tumors treated with PRRT

The “3M” Approach to Cardiovascular Infections: Multimodality, Multitracers, and Multidisciplinary

The Development of an Intelligent Agent to Detect and Non-Invasively Characterize Lung Lesions on CT Scans: Ready for the "Real World"?

Deep learning in Nuclear Medicine—focus on CNN-based approaches for PET/CT and PET/MR: where do we stand?

PSMA expression level predicts differentiated thyroid cancer aggressiveness and patient outcome

Image Embeddings Extracted from CNNs Outperform Other Transfer Learning Approaches in Classification of Chest Radiographs

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