Machine learning for differentiating metastatic and completely responded sclerotic bone lesion in prostate cancer: a retrospective radiomics study

E Acar, A Leblebici, BE Ellidokuz… - The British journal of …, 2019 - academic.oup.com
Objective: Using CT texture analysis and machine learning methods, this study aims to
distinguish the lesions imaged via 68Ga-prostate-specific membrane antigen (PSMA) …
被引用次数：60 相关文章

Machine learning for differentiating metastatic and completely responded sclerotic bone lesion in prostate cancer: a retrospective radiomics study.

E Acar, A Leblebici, BE Ellidokuz… - The British Journal of …, 2019 - europepmc.org
Objective Using CT texture analysis and machine learning methods, this study aims to
distinguish the lesions imaged via 68Ga-prostate-specific membrane antigen (PSMA) …
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[HTML][HTML] Machine learning for differentiating metastatic and completely responded sclerotic bone lesion in prostate cancer: a retrospective radiomics study

E Acar, A Leblebici, BE Ellidokuz… - The British Journal of …, 2019 - ncbi.nlm.nih.gov
Objective: Using CT texture analysis and machine learning methods, this study aims to
distinguish the lesions imaged via 68Ga-prostate-specific membrane antigen (PSMA) …

Machine learning for differentiating metastatic and completely responded sclerotic bone lesion in prostate cancer: a retrospective radiomics study

E Acar, A Leblebici, E Ellidokuz… - BRITISH JOURNAL …, 2019 - avesis.deu.edu.tr
Objective: Using CT texture analysis and machine learning methods, this study aims to
distinguish the lesions imaged via 68Ga-prostate-specific membrane antigen (PSMA) …

Machine learning for differentiating metastatic and completely responded sclerotic bone lesion in prostate cancer: a retrospective radiomics study

E Acar, A Leblebici, BE Ellidokuz… - The British journal …, 2019 - pubmed.ncbi.nlm.nih.gov
Objective Using CT texture analysis and machine learning methods, this study aims to
distinguish the lesions imaged via 68Ga-prostate-specific membrane antigen (PSMA) …