Machine Learning for Clinical Pathway Decision Support in Suspected Bone Lesions on Radiographs

Introduction: Incidental findings occur in up to 20% of conventional radiographs [ref:1]. The complex morphology of bone tumors, inflammatory changes, normal variants, or metastases can lead to unnecessary diagnostic escalation (MRI, contrast-enhanced imaging, scintigraphy) [ref:2]. [for full text, please go to the a.m. URL]

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Publication Details

Journal
German Medical Science (German Research Foundation)
Published
2025-11-03
DOI
https://doi.org/10.3205/25gmds095
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
0.00
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article

Machine Learning for Clinical Pathway Decision Support in Suspected Bone Lesions on Radiographs

German Medical Science (German Research Foundation)
Radiomics and Machine Learning in Medical Imaging
article

Machine Learning for Clinical Pathway Decision Support in Suspected Bone Lesions on Radiographs

article en

Abstract

Introduction: Incidental findings occur in up to 20% of conventional radiographs [ref:1]. The complex morphology of bone tumors, inflammatory changes, normal variants, or metastases can lead to unnecessary diagnostic escalation (MRI, contrast-enhanced imaging, scintigraphy) [ref:2]. [for full text, please go to the a.m. URL]

German Medical Science (German Research Foundation)
Berliner Hochschule für Technik (DE), Unfallkrankenhaus Berlin (DE), Berufsgenossenschaftliche Unfallklinik Frankfurt am Main (DE)
Peace, Justice and strong institutions
Openalex Percentile: Top 35%
Radiomics and Machine Learning in Medical Imaging
DOIOpen Access PDFOpenAlex
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