Radiomics of locally advanced rectal cancer: machine learning-based prediction of response to neoadj...
Radiomics of locally advanced rectal cancer: machine learning-based prediction of response to neoadjuvant chemoradiotherapy using pre-treatment sagittal T2-weighted MRI
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Publisher
Singapore: Springer Nature Singapore
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Language
English
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Publisher
Singapore: Springer Nature Singapore
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Purpose
Variable response to neoadjuvant chemoradiotherapy (nCRT) is observed among individuals with locally advanced rectal cancer (LARC), having a significant impact on patient management. In this work, we aimed to investigate the potential value of machine learning (ML)-based magnetic resonance imaging (MRI) radiomics in predicting therapeuti...
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Full title
Radiomics of locally advanced rectal cancer: machine learning-based prediction of response to neoadjuvant chemoradiotherapy using pre-treatment sagittal T2-weighted MRI
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TN_cdi_proquest_miscellaneous_2702178041
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_miscellaneous_2702178041
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ISSN
1867-1071
E-ISSN
1867-108X
DOI
10.1007/s11604-022-01325-7
