Machine learning prediction of effective radiation doses in various computed tomography applications: a virtual human phantom study

The LR was shown to be the best approach out of those used in the ML estimation of CT-induced doses.

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Publication Details

Journal
Biomedizinische Technik/Biomedical Engineering
Published
2025-04-08
DOI
https://doi.org/10.1515/bmt-2024-0620
Citations
1
Primary Topic
Radiation Dose and Imaging
Type
article
Field-Weighted Citation Impact
1.36
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article

Machine learning prediction of effective radiation doses in various computed tomography applications: a virtual human phantom study

Handan Tanyildizi-Kökkülünk
1 citations
Biomedizinische Technik/Biomedical Engineering
Radiation Dose and Imaging
1.36
article

Machine learning prediction of effective radiation doses in various computed tomography applications: a virtual human phantom study

Handan Tanyildizi-Kökkülünk
article en
1 citations

Abstract

The LR was shown to be the best approach out of those used in the ML estimation of CT-induced doses.

Biomedizinische Technik/Biomedical EngineeringVol. 70(4)
Altınbaş University (TR)
Openalex Percentile: Top 22%
Radiation Dose and Imaging
1.36
DOIOpen Access PDFOpenAlex
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Machine learning prediction of effective radiation doses in various computed tomography applications: a virtual human phantom study — Handan Tanyildizi-Kökkülünk · Biomedizinische Technik/Biomedical Engineering (2025) | TGRS Research Map | TGRS