Prognostic value of anthropometric measures extracted from whole-body CT using deep learning in patients with non-small-cell lung cancer
Author:
Publisher
Springer Science and Business Media LLC
Subject
Radiology, Nuclear Medicine and imaging,General Medicine
Link
http://link.springer.com/content/pdf/10.1007/s00330-019-06630-w.pdf
Reference32 articles.
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3. Hilmi M, Jouinot A, Burns R et al (2018) Body composition and sarcopenia: the next-generation of personalized oncology and pharmacology? Pharmacol Ther. https://doi.org/10.1016/j.pharmthera.2018.12.003
4. Brown JC, Harhay MO, Harhay MN (2018) Anthropometrically predicted visceral adipose tissue and blood-based biomarkers: a cross-sectional analysis. Eur J Nutr 57:191–198. https://doi.org/10.1007/s00394-016-1308-8
5. Mensink SD, Spliethoff JW, Belder R, Klaase JM, Bezooijen R, Slump CH (2011) Development of automated quantification of visceral and subcutaneous adipose tissue volumes from abdominal CT scans. Proc. SPIE 7963, Medical Imaging 2011. Computer-Aided Diagnosis:79632Q. https://doi.org/10.1117/12.878017
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