Computed tomography-based radiomics combined with machine learning allows differentiation between primary intestinal lymphoma and Crohn's disease.

Journal: World journal of gastroenterology

PMID: 39006389

Abstract

BACKGROUND: Due to similar clinical manifestations and imaging signs, differential diagnosis of primary intestinal lymphoma (PIL) and Crohn's disease (CD) is a challenge in clinical practice.

Authors

Meng-Jun Xiao

Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, Shandong Province, China.
Yu-Teng Pan

Medical Science and Technology Innovation Center, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan 250000, Shandong Province, China.
Jia-He Tan

University of California, Davis, CA 95616, United States.
Hai-Ou Li

Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong Province, China.
Hai-yan Wang

Keywords

Adult Aged Contrast Media Crohn Disease Diagnosis, Differential Female Humans Intestinal Neoplasms Lymphoma Machine Learning Male Middle Aged Radiomics Retrospective Studies ROC Curve Sensitivity and Specificity Tomography, X-Ray Computed Young Adult

External Resources

View on PubMed Access via DOI PubMed (39006389)

Computed tomography-based radiomics combined with machine learning allows differentiation between primary intestinal lymphoma and Crohn's disease.

Abstract

Authors

Keywords

External Resources

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