טוען...
Machine learning for differentiating metastatic and completely responded sclerotic bone lesion in prostate cancer: a retrospective radiomics study
OBJECTIVE: Using CT texture analysis and machine learning methods, this study aims to distinguish the lesions imaged via 68Ga-prostate-specific membrane antigen (PSMA) positron emission tomography (PET)/CT as metastatic and completely responded in patients with known bone metastasis and who were pre...
שמור ב:
| הוצא לאור ב: | Br J Radiol |
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| Main Authors: | , , , , |
| פורמט: | Artigo |
| שפה: | Inglês |
| יצא לאור: |
The British Institute of Radiology.
2019
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| נושאים: | |
| גישה מקוונת: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6732932/ https://ncbi.nlm.nih.gov/pubmed/31219712 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1259/bjr.20190286 |
| תגים: |
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