☆ 4.8 Article

Development of a deep learning-based nomogram for predicting lymph node metastasis in cervical cancer: A multicenter study

CLINICAL AND TRANSLATIONAL MEDICINE (2022)

Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries

Hyuna Sung et al.

Summary: The global cancer burden in 2020 saw an estimated 19.3 million new cancer cases and almost 10.0 million cancer deaths. Female breast cancer surpassed lung cancer as the most commonly diagnosed cancer, while lung cancer remained the leading cause of cancer death. These trends are expected to rise in 2040, with transitioning countries experiencing a larger increase compared to transitioned countries due to demographic changes and risk factors associated with globalization and a growing economy. Efforts to improve cancer prevention measures and provision of cancer care in transitioning countries will be crucial for global cancer control.

CA-A CANCER JOURNAL FOR CLINICIANS (2021)

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Article Oncology

Computed tomography-based radiomic model at node level for the prediction of normal-sized lymph node metastasis in cervical cancer

Yujia Liu et al.

Summary: This study developed a radiomic model based on computed tomography for the prediction of normal-sized lymph node metastasis in cervical cancer, showing promising results. The combination of features from two phases and the use of artificial neural network resulted in better performance of the radiomic model in training and internal validation cohorts. The model could potentially optimize clinical staging and decision-making processes.

TRANSLATIONAL ONCOLOGY (2021)

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Article Radiology, Nuclear Medicine & Medical Imaging

Noninvasive CT radiomic model for preoperative prediction of lymph node metastasis in early cervical carcinoma

Jiaming Chen et al.

BRITISH JOURNAL OF RADIOLOGY (2020)

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Editorial Material Radiology, Nuclear Medicine & Medical Imaging

Assessing Radiology Research on Artificial Intelligence: A Brief Guide for Authors, Reviewers, and Readers-From the Radiology Editorial Board

David A. Bluemke et al.

RADIOLOGY (2020)

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Article Radiology, Nuclear Medicine & Medical Imaging

Radiomic signature as a predictive factor for lymph node metastasis in early-stage cervical cancer

Yangyang Kan et al.

JOURNAL OF MAGNETIC RESONANCE IMAGING (2019)

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Review Oncology

Cervical Cancer, Version 3.2019

Wui-Jin Koh et al.

JOURNAL OF THE NATIONAL COMPREHENSIVE CANCER NETWORK (2019)

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Review Oncology

Lymph Node Assessment in Cervical Cancer: Prognostic and Therapeutic Implications

L. T. Gien et al.

JOURNAL OF SURGICAL ONCOLOGY (2009)

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Development of a deep learning-based nomogram for predicting lymph node metastasis in cervical cancer: A multicenter study

相关参考文献

Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries

Computed tomography-based radiomic model at node level for the prediction of normal-sized lymph node metastasis in cervical cancer

Noninvasive CT radiomic model for preoperative prediction of lymph node metastasis in early cervical carcinoma

Assessing Radiology Research on Artificial Intelligence: A Brief Guide for Authors, Reviewers, and Readers-From the Radiology Editorial Board

Radiomic signature as a predictive factor for lymph node metastasis in early-stage cervical cancer

Cervical Cancer, Version 3.2019

Lymph Node Assessment in Cervical Cancer: Prognostic and Therapeutic Implications

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