Performance of Statistical and Neural Network Method for Prediction of Survival of Oral Cancer Patients

2016 ◽  
pp. 263-284
Author(s):  
Neha Sharma ◽  
Hari Om
Keyword(s):  
Neural Network ◽  
Oral Cancer ◽  
Cancer Patients ◽  
Neural Network Method ◽  
Prediction Of Survival ◽  
Network Method ◽  
Oral Cancer Patients

Shunt Control on Smart Structures Using Genetic Algorithm and Neural Network Method.

2019 ◽  
Author(s):  
Venicio Silva Araujo ◽  
Guilherme Silva Prado ◽  
Heinsten Frederich Leal dos Santos
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Smart Structures ◽  
Neural Network Method ◽  
Network Method ◽  
Shunt Control

Methods for evaluation the manufacturability of a vehicle

2020 ◽  
pp. 152-160
Keyword(s):  
Neural Network ◽  
Initial Data ◽  
Comparative Data ◽  
Training Algorithm ◽  
Neural Network Method ◽  
The Neural Network ◽  
Network Method ◽  
Calculation Results ◽  
Production And Operation

Methods for evaluation the manufacturability of a vehicle in the field of production and operation based on an energy indicator, expert estimates and usage of a neural network are stated. By using the neural network method the manufacturability of a car in a complex and for individual units is considered. The preparation of the initial data at usage a neural network for predicting the manufacturability of a vehicle is shown; the training algorithm and the architecture for calculating the manufacturability of the main units are given. According to the calculation results, comparative data on the manufacturability vehicles of various brands are given.

scholarly journals The approximation neural-network method for solving nonlinear multi-criteria inverse problems of geophysics

2021 ◽  
Vol 1715 ◽  
pp. 012045
Author(s):  
M I Shimelevich ◽  
E A Obornev ◽  
I E Obornev ◽  
E A Rodionov
Keyword(s):  
Neural Network ◽  
Inverse Problems ◽  
Neural Network Method ◽  
Network Method

scholarly journals High Expression of KLF10 Is Associated with Favorable Survival in Patients with Oral Squamous Cell Carcinoma

Medicina ◽  
2020 ◽  
Vol 57 (1) ◽  
pp. 17
Author(s):  
Chung-Min Yeh ◽  
Yi-Ju Lee ◽  
Po-Yun Ko ◽  
Yueh-Min Lin ◽  
Wen-Wei Sung
Keyword(s):  
Survival Rate ◽  
Oral Cancer ◽  
Cancer Patients ◽  
Protective Factor ◽  
Female Gender ◽  
Vital Role ◽  
Cancer Stage ◽  
Independent Prognostic Marker ◽  
Oral Cancer Patients ◽  
The Impact

Background and objectives: Krüppel-like transcription factor 10 (KLF10) plays a vital role in regulating cell proliferation, including the anti-proliferative process, activation of apoptosis, and differentiation control. KLF10 may also act as a protective factor against oral cancer. We studied the impact of KLF10 expression on the clinical outcomes of oral cancer patients to identify its role as a prognostic factor in oral cancer. Materials and Methods: KLF10 immunoreactivity was analyzed by immunohistochemical (IHC) stain analysis in 286 cancer specimens from primary oral cancer patients. The prognostic value of KLF10 on overall survival was determined by Kaplan–Meier analysis and the Cox proportional hazard model. Results: High KLF10 expression was significantly associated with male gender and betel quid chewing. The 5-year survival rate was greater for patients with high KLF10 expression than for those with low KLF10 expression (62.5% vs. 51.3%, respectively; p = 0.005), and multivariate analyses showed that high KLF10 expression was the only independent factor correlated with greater overall patient survival. The significant correlation between high KLF10 expression and a higher 5-year survival rate was observed in certain subgroups of clinical parameters, including female gender, non-smokers, cancer stage T1, and cancer stage N0. Conclusions: KLF10 expression, detected by IHC staining, could be an independent prognostic marker for oral cancer patients.

scholarly journals Genetic Variants of lncRNA GAS5 Are Associated with the Clinicopathologic Development of Oral Cancer

2021 ◽  
Vol 11 (5) ◽  
pp. 348
Author(s):  
Ming-Hong Hsieh ◽  
Hsueh-Ju Lu ◽  
Chiao-Wen Lin ◽  
Chia-Yi Lee ◽  
Shang-Jung Yang ◽  
...  
Keyword(s):  
Cell Differentiation ◽  
Oral Cancer ◽  
Cancer Patients ◽  
Alcohol Drinking ◽  
Tumor Size ◽  
Genetic Variants ◽  
Tumor Stage ◽  
Advanced Tumor Stage ◽  
Advanced Tumor ◽  
Oral Cancer Patients

The long noncoding RNA, Growth arrest-specific 5 (GAS5) plays a crucial role in the development of oral cancer. However, potential genetic variants in GAS5 that affect the susceptibility and progression of oral cancer have rarely been explored. In this study, two loci of GAS5 single nucleotide polymorphisms (SNPs) (rs145204276 and rs55829688) were genotyped by using the TaqMan allelic discrimination in 1125 oral cancer patients and 1195 non-oral-cancer individuals. After statistical analyses, the distribution of both the GAS5 SNP rs145204276 and GAS5 SNP rs55829688 frequencies were similar between the study and control groups. However, the patients with GAS5 SNP rs145204276 variants (Ins/Del or Del/Del) showed a higher tendency of moderate to poor cell differentiation of oral cancer (OR: 1.454, 95% CI: 1.041–2.031, p = 0.028). Moreover, the GAS5 SNP rs145204276 variants (Ins/Del or Del/Del) in the non-alcohol-drinking population were associated with significantly advanced tumor stage (OR: 1.500, 95% CI: 1.081–2.081, p = 0.015) and larger tumor size (OR: 1.494, 95% CI: 1.076–2.074, p = 0.016). Furthermore, individuals with the GAS5 SNP rs145204276 variant were associated with a higher expression of GAS5 in the GTEx database (p = 0.002), and the higher GAS5 level was associated with poor cell differentiation, advanced tumor stage and larger tumor size in head and neck squamous cell carcinoma from the TCGA database (all p < 0.05). In conclusion, the GAS5 SNP rs145204276 variant is related to poor-differentiation cell status in oral cancer. Besides, the presence of the GAS5 SNP rs145204276 variant is associated with a worse tumor stage and tumor size in oral cancer patients without alcohol drinking.

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