Clinical application of PET radiomics and artificial intelligence in non-small cell lung cancer
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Clinical application of PET radiomics and artificial intelligence in non-small cell lung cancer
Journal of Chongqing Medical UniversityVol. 43, Issue 11, Pages: 1519-1522(2018)
作者机构:
中国医学科学院北京协和医学院北京协和医院核医学科
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Published:2018,
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Wang Jingnan, Huo Li, Li Fang. Clinical application of PET radiomics and artificial intelligence in non-small cell lung cancer. [J]. Journal of Chongqing Medical University 43(11):1519-1522(2018)
DOI:
Wang Jingnan, Huo Li, Li Fang. Clinical application of PET radiomics and artificial intelligence in non-small cell lung cancer. [J]. Journal of Chongqing Medical University 43(11):1519-1522(2018)DOI:
Clinical application of PET radiomics and artificial intelligence in non-small cell lung cancer
Radiomics is an evolving field in which extraction and screening a large amount of image features could be used to estab-lish predictive models with clinical information through artificial intelligence technology and statistical analysis,thereby improving the diagnostic accuracy,predicting treatment response and prognostication,potentially allowing personalized cancer therapy. As a promis-ing new field,radiomics has broad application prospects. This review will focus on the overview,current status,process and challenges in the clinical application of PET radiomics in non-small cell lung cancer.
关键词
核医学影像组学图像特征模型构建非小细胞肺癌
Keywords
PET radiomicsimage featurespredictive model buildingnon-small cell lung cancer
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Efficacy and safety of EFGR tyrosine kinase inhibitor monotherapy with docetaxel monotherapy in previously treated advanced non-small-cell lung cancer:a Meta-analysis
Long non-coding RNA MIR155HG promotes proliferation,migration and invasion of A549 human lung cancer cells
Clinical efficacy of IMRT combined with late course stereotactic body radiotherapy for local middle-late stage non-small cell lung cancer
Association of OCT4 positive expression with clinic-pathological characteristics in non-small cell lung cancer: a Meta-analysis
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