4.6 Article

A machine learning-based PET/CT model for automatic diagnosis of early-stage lung cancer

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Article Engineering, Biomedical

An investigation of CNN models for differentiating malignant from benign lesions using small pathologically proven datasets

Shu Zhang et al.

COMPUTERIZED MEDICAL IMAGING AND GRAPHICS (2019)

Article Cardiac & Cardiovascular Systems

Prognostic impact of a ground glass opacity component in the clinical T classification of non-small cell lung cancer

Aritoshi Hattori et al.

JOURNAL OF THORACIC AND CARDIOVASCULAR SURGERY (2017)

Review Endocrinology & Metabolism

Genomic and epigenomic mechanisms of glucocorticoids in the brain

Jason D. Gray et al.

NATURE REVIEWS ENDOCRINOLOGY (2017)

Article Radiology, Nuclear Medicine & Medical Imaging

Employing 18F-FDGPET/CT for distinguishing benign from metastatic adrenal masses

Rania Refaat et al.

EGYPTIAN JOURNAL OF RADIOLOGY AND NUCLEAR MEDICINE (2017)

Article Biology

Predictive significance of standardized uptake value parameters of FDG-PET in patients with non-small cell lung carcinoma

X. -Y. Duan et al.

BRAZILIAN JOURNAL OF MEDICAL AND BIOLOGICAL RESEARCH (2015)

Article Radiology, Nuclear Medicine & Medical Imaging

Overestimated value of 18F- FDG PET/ CT to diagnose pulmonary nodules: Analysis of 298 patients

S. Li et al.

CLINICAL RADIOLOGY (2014)

Article Statistics & Probability

Statistical Models: Theory and Practice, Revised Edition by David A. Freedman

Terry Speed

INTERNATIONAL STATISTICAL REVIEW (2010)

Review Oncology

Medical management of brain metastases from lung cancer

Ryuya Yamanaka

ONCOLOGY REPORTS (2009)

Article Radiology, Nuclear Medicine & Medical Imaging

Malignant versus benign nodules at CT screening for lung cancer: Comparison of thin-section CT findings

F Li et al.

RADIOLOGY (2004)