Radiomics-based machine learning in the differentiation of benign and malignant bowel wall thickening radiomics in bowel wall thickening.

Journal: Japanese journal of radiology

Published Date: Mar 27, 2024

Abstract

PURPOSE: To distinguish malignant and benign bowel wall thickening (BWT) by using computed tomography (CT) texture features based on machine learning (ML) models and to compare its success with the clinical model and combined model.

Authors

Hande Melike Bülbül

Department of Radiology, Ministry of Health Recep Tayyip Erdoğan University Training and Research Hospital, Rize, Turkey. handemelikehalac@gmail.com.
Gülen Burakgazi

Department of Radiology, Ministry of Health Recep Tayyip Erdoğan University Training and Research Hospital, Rize, Turkey.
Uğur Kesimal

Department of Radiology, Ankara Training and Research Hospital, Ankara, Türkiye.
Esat Kaba

Radiology, Recep Tayyip Erdoğan Education and Research Hospital, Rize, TUR.

Keywords

Adult Aged Aged, 80 and over Colonoscopy Contrast Media Diagnosis, Differential Female Humans Machine Learning Male Middle Aged Radiographic Image Interpretation, Computer-Assisted Radiomics Retrospective Studies Tomography, X-Ray Computed

External Resources

View on PubMed Access via DOI PubMed (38536559)

Radiomics-based machine learning in the differentiation of benign and malignant bowel wall thickening radiomics in bowel wall thickening.

Abstract

Authors

Keywords

External Resources

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