Last Posted: Sep 07, 2021
- A convolutional neural network combined with positional and textural attention for the fully automatic delineation of primary nasopharyngeal carcinoma on non-contrast-enhanced MRI.
Wong Lun M et al. Quantitative imaging in medicine and surgery 2021 11(9) 3932-3944
- A deep learning-based radiomic nomogram for prognosis and treatment decision in advanced nasopharyngeal carcinoma: A multicentre study.
Zhong Lianzhen et al. EBioMedicine 2021 70103522
- Radiomics Model to Predict Early Progression of Nonmetastatic Nasopharyngeal Carcinoma after Intensity Modulation Radiation Therapy: A Multicenter Study.
Du Richard et al. Radiology. Artificial intelligence 2019 1(4) e180075
- A Prognostic Predictive System Based on Deep Learning for Locoregionally Advanced Nasopharyngeal Carcinoma.
Qiang Mengyun et al. Journal of the National Cancer Institute 2020 Sep
- Combination of RERG and ZNF671 methylation rates in circulating cell-free DNA: A novel biomarker for screening of nasopharyngeal carcinoma.
Xu Yifei et al. Cancer science 2020 Jul 111(7) 2536-2545
- Germline Polymorphisms and Length of Survival of Nasopharyngeal Carcinoma: An Exome-Wide Association Study in Multiple Cohorts.
Guo Yun-Miao et al. Advanced science (Weinheim, Baden-Wurttemberg, Germany) 2020 May 7(10) 1903727
- Clinical utility of serial analysis of circulating tumour cells for detection of minimal residual disease of metastatic nasopharyngeal carcinoma.
Ko Josephine Mun-Yee et al. British journal of cancer 2020 May
- Computer-Aided Pathological Diagnosis of Nasopharyngeal Carcinoma Based on Deep Learning.
Diao Songhui et al. The American journal of pathology 2020 Apr
- Effect of machine learning re-sampling techniques for imbalanced datasets in 18 F-FDG PET-based radiomics model on prognostication performance in cohorts of head and neck cancer patients.
Xie Chenyi et al. European journal of nuclear medicine and molecular imaging 2020 Apr
- Fully-Automated Segmentation of Nasopharyngeal Carcinoma on Dual-Sequence MRI Using Convolutional Neural Networks.
Ye Yufeng et al. Frontiers in oncology 2020 10166
Rare Disease PHGKB is an online, continuously updated, searchable database of published scientific literature, CDC and NIH resources, and other information that address the public health impact and translation of genomic and other precision health discoveries into improved health outcomes related to rare diseases...more
Selected Rare Diseases
- Alpha-1 Antitrypsin Deficiency
- Amyotrophic Lateral Sclerosis
- Brugada Syndrome
- Cerebral Palsy
- Cystic Fibrosis
- Duchenne Muscular Dystrophy
- Erythema Multiforme
- Familial Mediterranean Fever
- Fragile X Syndrome
- Gaucher Disease
- Graves Disease
- Huntington Disease
- Myasthenia Gravis
- Retinitis Pigmentosa
- Severe Combined Immunodeficiency
Disclaimer: Articles listed in the Public Health Knowledge Base are selected by the CDC Office of Public Health Genomics to provide current awareness of the literature and news. Inclusion in the update does not necessarily represent the views of the Centers for Disease Control and Prevention nor does it imply endorsement of the article's methods or findings. CDC and DHHS assume no responsibility for the factual accuracy of the items presented. The selection, omission, or content of items does not imply any endorsement or other position taken by CDC or DHHS. Opinion, findings and conclusions expressed by the original authors of items included in the update, or persons quoted therein, are strictly their own and are in no way meant to represent the opinion or views of CDC or DHHS. References to publications, news sources, and non-CDC Websites are provided solely for informational purposes and do not imply endorsement by CDC or DHHS.