Oral Squamous Cell Carcinoma
What's New
Last Posted: May 07, 2024
- Survival estimation of oral cancer using fuzzy deep learning.
Rachasak Somyanonthanakul et al. BMC Oral Health 2024 24(1) 519 - Effects of tobacco on the DNA of smokers and non-smokers affected by OSCC: systematic review and meta-analysis.
Schuch Lauren Frenzel et al. Brazilian oral research 2023 37e008 - Intraoperative Assessment of Tumor Margins in Tissue Sections with Hyperspectral Imaging and Machine Learning.
Pertzborn David et al. Cancers 2023 15(1) - Novel Machine Learning Model to Predict Interval of Oral Cancer Recurrence for Surveillance Stratification.
Bourdillon Alexandra T et al. The Laryngoscope 2022 - Automatic classification and detection of oral cancer in photographic images using deep learning algorithms.
Warin Kritsasith et al. Journal of oral pathology & medicine : official publication of the International Association of Oral Pathologists and the American Academy of Oral Pathology 2021 - Machine learning in oral squamous cell carcinoma: Current status, clinical concerns and prospects for future-A systematic review.
Alabi Rasheed Omobolaji et al. Artificial intelligence in medicine 2021 115102060 - Development of a machine learning model for the prediction of nodal metastasis in early T classification oral squamous cell carcinoma: A SEER-based population study.
Kwak Min Seob et al. Head & neck 2021 - Revisiting the metallothionein genes polymorphisms and the risk of oral squamous cell carcinoma in a Brazilian population.
Rosa R-R et al. Medicina oral, patologia oral y cirugia bucal 2020 Dec - A Novel RNA-Seq-Based Model for Preoperative Prediction of Lymph Node Metastasis in Oral Squamous Cell Carcinoma.
Qiao Bo et al. BioMed research international 2020 20204252580 - Machine Learning and Treatment Outcome Prediction for Oral Cancer.
Chu Chui Shan et al. Journal of oral pathology & medicine : official publication of the International Association of Oral Pathologists and the American Academy of Oral Pathology 2020 Aug
More
About Rare Diseases PHGKB
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
Content Summary
Selected Rare Diseases
- Alpha-1 Antitrypsin Deficiency
- Amyotrophic Lateral Sclerosis
- Brugada Syndrome
- Cerebral Palsy
- Cystic Fibrosis
- Duchenne Muscular Dystrophy
- Eclampsia
- Erythema Multiforme
- Familial Mediterranean Fever
- Fragile X Syndrome
- Gaucher Disease
- Glomerulonephritis
- Graves Disease
- Hemophilia
- Huntington Disease
- Microcephaly
- Myasthenia Gravis
- Phenylketonuria
- Retinitis Pigmentosa
- Severe Combined Immunodeficiency
Disclaimer: Articles listed in the Public Health Knowledge Base are selected by Public Health Genomics Branch 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.
- Page last reviewed:Feb 1, 2024
- Content source: