Machine learning vs. radiomics for discriminating atypical cartilaginous tumors from benign enchondromas on MRI

In this pilot study, we demonstrated that MRI information alone can be used to differentiate between ACT and EC with high accuracy. These results seem promising that in future, machine learning and AI can be used for better orthopedic diagnosis of cartilaginous tumors in clinical practice.

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Publication Details

Journal
BioMedical Engineering OnLine
Published
2026-03-24
DOI
https://doi.org/10.1186/s12938-026-01547-0
Primary Topic
Bone Tumor Diagnosis and Treatments
Type
article
Field-Weighted Citation Impact
0.00
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article

Machine learning vs. radiomics for discriminating atypical cartilaginous tumors from benign enchondromas on MRI

BioMedical Engineering OnLine
Bone Tumor Diagnosis and Treatments
article

Machine learning vs. radiomics for discriminating atypical cartilaginous tumors from benign enchondromas on MRI

article en

Abstract

In this pilot study, we demonstrated that MRI information alone can be used to differentiate between ACT and EC with high accuracy. These results seem promising that in future, machine learning and AI can be used for better orthopedic diagnosis of cartilaginous tumors in clinical practice.

BioMedical Engineering OnLine
Medical University of Graz (AT), Geriatrische Gesundheitszentren (AT)
Reduced inequalities
Openalex Percentile: Top 10%
Bone Tumor Diagnosis and Treatments
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Machine learning vs. radiomics for discriminating atypical cartilaginous tumors from benign enchondromas on MRI · BioMedical Engineering OnLine (2026) | TGRS Research Map | TGRS