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Alessandro Bevilacqua

Showing results (41-50 of 48) with videos related to

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Cancers|April 12, 2022
Automatically Extracted Machine Learning Features from Preoperative CT to Early Predict Microvascular Invasion in HCC: The Role of the Zone of Transition (ZOT)Matteo Renzulli, Margherita Mottola, Francesca Coppola, et al.
Cancers|December 23, 2022
Beyond Multiparametric MRI and towards Radiomics to Detect Prostate Cancer: A Machine Learning Model to Predict Clinically Significant LesionsCaterina Gaudiano, Margherita Mottola, Lorenzo Bianchi, et al.
Journal of Clinical Medicine|March 11, 2023
Radiomic Features from Post-Operative <sup>18</sup>F-FDG PET/CT and CT Imaging Associated with Locally Recurrent Rectal Cancer: Preliminary FindingsDajana Cuicchi, Margherita Mottola, Paolo Castellucci, et al.
Biomedicines|January 15, 2021
Identification of Sclerostin as a Putative New Myokine Involved in the Muscle-to-Bone CrosstalkMaria Sara Magarò, Jessika Bertacchini, Francesca Florio, et al.
Cancers|July 14, 2023
An Apparent Diffusion Coefficient-Based Machine Learning Model Can Improve Prostate Cancer Detection in the Grey Area of the Prostate Imaging Reporting and Data System Category 3: A Single-Centre ExperienceCaterina Gaudiano, Margherita Mottola, Lorenzo Bianchi, et al.
Frontiers in Psychology|October 15, 2021
Human, All Too Human? An All-Around Appraisal of the "Artificial Intelligence Revolution" in Medical ImagingFrancesca Coppola, Lorenzo Faggioni, Michela Gabelloni, et al.
Journal of Experimental & Clinical Cancer Research : CR|March 6, 2021
TP53 drives abscopal effect by secretion of senescence-associated molecular signals in non-small cell lung cancerAnna Tesei, Chiara Arienti, Gianluca Bossi, et al.
Diagnostics (Basel, Switzerland)|April 30, 2021
The Heterogeneity of Skewness in T2W-Based Radiomics Predicts the Response to Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal CancerFrancesca Coppola, Margherita Mottola, Silvia Lo Monaco, et al.
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Showing results (41-50 of 48) with videos related to

Sort By:
Pageof 5
You have reached the last page of results.This site can display upto 48 results.
Cancers|April 12, 2022
Automatically Extracted Machine Learning Features from Preoperative CT to Early Predict Microvascular Invasion in HCC: The Role of the Zone of Transition (ZOT)Matteo Renzulli, Margherita Mottola, Francesca Coppola, et al.
Cancers|December 23, 2022
Beyond Multiparametric MRI and towards Radiomics to Detect Prostate Cancer: A Machine Learning Model to Predict Clinically Significant LesionsCaterina Gaudiano, Margherita Mottola, Lorenzo Bianchi, et al.
Journal of Clinical Medicine|March 11, 2023
Radiomic Features from Post-Operative <sup>18</sup>F-FDG PET/CT and CT Imaging Associated with Locally Recurrent Rectal Cancer: Preliminary FindingsDajana Cuicchi, Margherita Mottola, Paolo Castellucci, et al.
Biomedicines|January 15, 2021
Identification of Sclerostin as a Putative New Myokine Involved in the Muscle-to-Bone CrosstalkMaria Sara Magarò, Jessika Bertacchini, Francesca Florio, et al.
Cancers|July 14, 2023
An Apparent Diffusion Coefficient-Based Machine Learning Model Can Improve Prostate Cancer Detection in the Grey Area of the Prostate Imaging Reporting and Data System Category 3: A Single-Centre ExperienceCaterina Gaudiano, Margherita Mottola, Lorenzo Bianchi, et al.
Frontiers in Psychology|October 15, 2021
Human, All Too Human? An All-Around Appraisal of the "Artificial Intelligence Revolution" in Medical ImagingFrancesca Coppola, Lorenzo Faggioni, Michela Gabelloni, et al.
Journal of Experimental & Clinical Cancer Research : CR|March 6, 2021
TP53 drives abscopal effect by secretion of senescence-associated molecular signals in non-small cell lung cancerAnna Tesei, Chiara Arienti, Gianluca Bossi, et al.
Diagnostics (Basel, Switzerland)|April 30, 2021
The Heterogeneity of Skewness in T2W-Based Radiomics Predicts the Response to Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal CancerFrancesca Coppola, Margherita Mottola, Silvia Lo Monaco, et al.
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