Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Jia Yan Tan"'
Predicting Overall Survival Using Machine Learning Algorithms in Oral Cavity Squamous Cell Carcinoma
Publikováno v:
Anticancer Research. 42:5859-5866
Machine learning (ML) models are often modelled to predict cancer prognosis but rarely consider spatial factors in a region. Hence this study explored machine learning algorithms utilising Local Government Areas (LGAs) in Queensland, Australia to spa
Publikováno v:
Head & Neck.
Publikováno v:
Clinical Oral Investigations. 25:6909-6918
To compare the treatment response and prognosis of oral cavity cancer between non-smoking and non-alcohol-drinking (NSND) patients and smoking and alcohol-drinking (SD) patients. A total of 313 consecutively treated patients from 2000 to 2019 were in
Autor:
John Adeoye, Abdulrahman Sakeen Alkandari, Jia Yan Tan, Weilan Wang, Wang‐Yong Zhu, Peter Thomson, Li‐Wu Zheng, Siu‐Wai Choi, Yu‐Xiong Su
Publikováno v:
Journal of oral pathologymedicine : official publication of the International Association of Oral Pathologists and the American Academy of Oral PathologyREFERENCES. 51(5)
Impact and efficiency of oral cancer and oral potentially malignant disorders screening are most realized in "at-risk" individuals. However, tools that can provide essential knowledge on individuals' risks are not applied in risk-based screening. Thi
Publikováno v:
HeadneckREFERENCES. 43(11)
Oral cavity cancer is often described as a lifestyle-related malignancy due to its strong associations with habitual factors, including tobacco use, heavy alcohol consumption, and betel nut chewing. However, patients with no genetically predisposing
Publikováno v:
International journal of medical informatics. 154
Objectives Machine learning platforms are now being introduced into modern oncological practice for classification and prediction of patient outcomes. To determine the current status of the application of these learning models as adjunctive decision-
Publikováno v:
International journal of medical informatics. 157
Background Applying machine learning to predicting oral cavity cancer prognosis is important in selecting candidates for aggressive treatment following diagnosis. However, models proposed so far have only considered cancer survival as discrete rather
Autor:
Susan Yung, Jia Yan Tan, Joyce Man-Fong Lee, Raymond Chuen-Chung Chang, Yuen Shan Ho, Chi Fai Lau, Krit Lee
Publikováno v:
Brain research bulletin. 169
Introduction Cognitive impairment is a common complication in chronic kidney disease (CKD) patients. Currently, limited types of animal models are available for studying cognitive impairment in CKD. We used unilateral ureteral obstruction (UUO) in mi