Non-invasive PNET grading using CT radiomics and machine learning

Non-invasive PNET grading using CT radiomics and machine learning

Pancreatic cancer is a major cause of cancer-related fatalities globally, with a poor prognosis. Machine learning-based medical image analysis has emerged as a promising approach for improving clinical decision-making. The purpose is to determine the most effective machine learning method and phase...

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Bibliographic Details
Main Authors: Faeze Salahshour, Mahsa Taherzadeh, Ghasem Hajianfar, Gholamreza Bayat, Farid Azmoudeh Ardalan, Soroush Bagheri, Arman Esmailzadeh, Majid Kahe, Sajad P. Shayesteh
Format: Article
Language:English
Published: Taylor & Francis Group 2025-12-01
Series:Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization
Subjects:
Pancreatic neuroendocrine tumors
radiomics
CT
pathological grading
machine learning
Online Access:https://www.tandfonline.com/doi/10.1080/21681163.2025.2500429
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https://www.tandfonline.com/doi/10.1080/21681163.2025.2500429

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