Alessandro Bevilacqua

Bologna, Italy

Last Updated: 09/26/2026

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Found 43 publications

Computer-Based Detection of Colorectal Serrated Lesions: Digital Flatness, a Novel Metric Designed for Whole-Slide Images.

Computer-Based Detection of Colorectal Serrated Lesions: Digital Flatness, a Novel Metric Designed for Whole-Slide Images.

Journal: Laboratory investigation; a journal of technical methods and pathology

Published: December 02, 2024

The Effectiveness of an Adaptive Method to Analyse the Transition between Tumour and Peritumour for Answering Two Clinical Questions in Cancer Imaging.

The Effectiveness of an Adaptive Method to Analyse the Transition between Tumour and Peritumour for Answering Two Clinical Questions in Cancer Imaging.

Journal: Sensors (Basel, Switzerland)

Published: December 28, 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 Experience.

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 Experience.

Journal: Cancers

Published: May 22, 2023

Radiomic Features from Post-Operative 18F-FDG PET/CT and CT Imaging Associated with Locally Recurrent Rectal Cancer: Preliminary Findings.

Radiomic Features from Post-Operative 18F-FDG PET/CT and CT Imaging Associated with Locally Recurrent Rectal Cancer: Preliminary Findings.

Journal: Journal of clinical medicine

Published: February 14, 2023

Beyond Multiparametric MRI and towards Radiomics to Detect Prostate Cancer: A Machine Learning Model to Predict Clinically Significant Lesions.

Beyond Multiparametric MRI and towards Radiomics to Detect Prostate Cancer: A Machine Learning Model to Predict Clinically Significant Lesions.

Journal: Cancers

Published: November 08, 2022

Letter to the Editor on "Comparative performance of fully-automated and semi-automated artificial intelligence methods for the detection of clinically significant prostate cancer on MRI: a systematic review".

Letter to the Editor on "Comparative performance of fully-automated and semi-automated artificial intelligence methods for the detection of clinically significant prostate cancer on MRI: a systematic review".

Journal: Insights into imaging

Published: August 10, 2022

Pro-inflammatory RNA:DNA Hybrids Are p53 Independently Boosted by Hyperbaric Oxygen: a Subcellular Distribution Analysis by Automated Quantitative Imaging.

Pro-inflammatory RNA:DNA Hybrids Are p53 Independently Boosted by Hyperbaric Oxygen: a Subcellular Distribution Analysis by Automated Quantitative Imaging.

Journal: Molecular imaging and biology

Published: July 20, 2022

Automatically Extracted Machine Learning Features from Preoperative CT to Early Predict Microvascular Invasion in HCC: The Role of the Zone of Transition (ZOT).

Automatically Extracted Machine Learning Features from Preoperative CT to Early Predict Microvascular Invasion in HCC: The Role of the Zone of Transition (ZOT).

Journal: Cancers

Published: February 21, 2022

Co-Density Distribution Maps for Advanced Molecule Colocalization and Co-Distribution Analysis.

Co-Density Distribution Maps for Advanced Molecule Colocalization and Co-Distribution Analysis.

Journal: Sensors (Basel, Switzerland)

Published: July 28, 2021

Human, All Too Human? An All-Around Appraisal of the "Artificial Intelligence Revolution" in Medical Imaging.

Human, All Too Human? An All-Around Appraisal of the "Artificial Intelligence Revolution" in Medical Imaging.

Journal: Frontiers in psychology

Published: May 18, 2021

A [68Ga]Ga-DOTANOC PET/CT Radiomic Model for Non-Invasive Prediction of Tumour Grade in Pancreatic Neuroendocrine Tumours.

A [68Ga]Ga-DOTANOC PET/CT Radiomic Model for Non-Invasive Prediction of Tumour Grade in Pancreatic Neuroendocrine Tumours.

Journal: Diagnostics (Basel, Switzerland)

Published: April 26, 2021

The Heterogeneity of Skewness in T2W-Based Radiomics Predicts the Response to Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer.

The Heterogeneity of Skewness in T2W-Based Radiomics Predicts the Response to Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer.

Journal: Diagnostics (Basel, Switzerland)

Published: March 18, 2021

Showing 1-12 of 43

Last Updated: 09/26/2026