scholarly journals Comparison between artificial neural network and Cox regression model in predicting the survival rate of gastric cancer patients

2013 ◽  
Vol 1 (5) ◽  
pp. 757-760 ◽  
Author(s):  
LUCHENG ZHU ◽  
WENHUA LUO ◽  
MENG SU ◽  
HANGPING WEI ◽  
JUAN WEI ◽  
...  
Keyword(s):  
Neural Network ◽  
Gastric Cancer ◽  
Artificial Neural Network ◽  
Survival Rate ◽  
Regression Model ◽  
Cancer Patients ◽  
Cox Regression ◽  
Cox Regression Model ◽  
Artificial Neural ◽  
Gastric Cancer Patients

scholarly journals Artificial neural network, predictor variables and sensitivity threshold for DNA methylation-based age prediction using blood samples

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Zhonghui Thong ◽  
Jolena Ying Ying Tan ◽  
Eileen Shuzhen Loo ◽  
Yu Wei Phua ◽  
Xavier Liang Shun Chan ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Regression Model ◽  
Sensitivity Threshold ◽  
Ann Model ◽  
Blood Samples ◽  
Ann Models ◽  
Artificial Neural ◽  
The Impact ◽  
Age Prediction

AbstractRegression models are often used to predict age of an individual based on methylation patterns. Artificial neural network (ANN) however was recently shown to be more accurate for age prediction. Additionally, the impact of ethnicity and sex on our previous regression model have not been studied. Furthermore, there is currently no age prediction study investigating the lower limit of input DNA at the bisulfite treatment stage prior to pyrosequencing. Herein, we evaluated both regression and ANN models, and the impact of ethnicity and sex on age prediction for 333 local blood samples using three loci on the pyrosequencing platform. Subsequently, we trained a one locus-based ANN model to reduce the amount of DNA used. We demonstrated that the ANN model has a higher accuracy of age prediction than the regression model. Additionally, we showed that ethnicity did not affect age prediction among local Chinese, Malays and Indians. Although the predicted age of males were marginally overestimated, sex did not impact the accuracy of age prediction. Lastly, we present a one locus, dual CpG model using 25 ng of input DNA that is sufficient for forensic age prediction. In conclusion, the two ANN models validated would be useful for age prediction to provide forensic intelligence leads.

The Artificial Neural Network and Regression Analysis Approach to Prediction of the Fiber Diameter of Spunbonding Fabrics

2010 ◽  
Vol 33 ◽  
pp. 74-78
Author(s):  
B. Zhao
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Regression Model ◽  
Network Model ◽  
Process Parameters ◽  
Neural Network Model ◽  
Artificial Neural Network Model ◽  
Fiber Diameter ◽  
Statistical Regression ◽  
Artificial Neural

In this work, the artificial neural network model and statistical regression model are established and utilized for predicting the fiber diameter of spunbonding nonwovens from the process parameters. The artificial neural network model has good approximation capability and fast convergence rate, which is used in this research. The results show the artificial neural network model can provide quantitative predictions of fiber diameter and yield more accurate and stable predictions than the statistical regression model, which reveals that the artificial neural network model is based on the inherent principles, and it can yield reasonably good prediction results and provide insight into the relationship between process parameters and fiber diameter.

Expression and Clinical Significance of Serum Exosomal miR-375 in Patients with Gastric Cancer

2021 ◽  
Vol 7 (5) ◽  
pp. 3896-3904
Author(s):  
Daoting Deng ◽  
Hong Zhang ◽  
Junxi Liu ◽  
Lina Ma ◽  
Xinrui Lei ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Cancer Patients ◽  
Cox Regression ◽  
Prognostic Significance ◽  
Cox Regression Analysis ◽  
Healthy Group ◽  
Cancer Group ◽  
Kaplan Meier ◽  
Gastric Cancer Patients ◽  
Gastric Cancer Group

To explore exosomal miR-375 expression in gastric cancer patients and its relationship with patient prognosis. A total of 53 patients diagnosed with gastric cancer in our hospital from May 2014 to May 2016 were included as the gastric cancer group, and 46 healthy women who came to our hospital for physical examination during the same period were enrolled as the healthy group. Exosomal miR-375 expression level was detected using qRT-PCR, and the diagnostic performance and prognostic significance of exosomal miR-375 in gastric cancer were explored. The gastric cancer group showed increased exosomal miR-375 expression than the healthy group (P< 0.05); Kaplan-Meier survival analysis exhibited that serum exosomal miR-375 has an AUC of 0.778, sensitivity of 69.57%, and specificity of 75.47%, whereas Cox regression analysis showed that the miR-375 expression in exosomes was an independent risk factor affecting the prognosis of gastric cancer patients (P< 0.05). Patient with gastric cancer showed upregulated miR-375 expression in serum exosomes. Serum exosomal miR-375 was found to has positive sensitivity and specificity in the diagnosis of gastric cancer, which may be associated with poor prognosis of gastric cancer patients.

scholarly journals Efficacy and Safety of FLOT regimen vs. DCF, FOLFOX, and ECF regimens as Perioperative Chemotherapy Treatments for Resectable Gastric Cancer Patients

2021 ◽  
Author(s):  
Pegah Farrokhi ◽  
Alireza Sadeghi ◽  
Mehran sharifi ◽  
Payam Dadvand ◽  
Rachel Riechelmann ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Overall Survival ◽  
Cancer Patients ◽  
Cox Regression ◽  
Progression Free Survival ◽  
R0 Resection ◽  
P Value ◽  
Perioperative Chemotherapy ◽  
Resectable Gastric Cancer ◽  
Gastric Cancer Patients

AbstractAimThis study aimed to evaluate and compare the efficacy and toxicity of common regimens used as perioperative chemotherapy including ECF, DCF, FOLFOX, and FLOT to identify the most effective chemotherapy regimen with less toxicity.Material and MethodsThis retrospective cohort study was based on 152 eligible gastric cancer patients recruited in a tertiary oncology hospital in Isfahan, Iran (2014-2019). All resectable gastric cancer patients who had received one of the four chemotherapy regimens including ECF, DCF, FOLFOX, or FLOT, and followed for at least one year (up to five years) were included. The primary endpoint of this study was Overall Survival (OS), Progression-Free Survival (PFS), Overall Response Rate (ORR), and R0 resection. We also considered toxicity according to CTCAE (v.4.0) criteria as a secondary endpoint. Cox -regression models were used applied to estimate OS and PFS time, controlled for relevant covariates.ResultsOf included patients, 32(21%), 51(33.7%), 37(24.3%), and 32(21%) had received ECF, DCF, FOLFOX and FLOT, respectively. After the median 25 months follow-up, overall survival was higher with the FLOT regimen in comparison with other regimens (hazard ratio [HR] = 0. 052). The median OS of the FLOT regimen was not reachable in Kaplan-Meier analysis and the median OS was 28, 26, and 23 months for DCF, FOLOFX, and ECF regimens, respectively. On the other hand, a median PFS of 25, 17, 15, and 14 months was observed for FLOT, DCF, FOLFOX, and ECF regimens, respectively (Log-rank = 0. 021). FLOT regimen showed 84. 4% ORR which was notably higher than other groups (p-value<0. 01).ConclusionsFor resectable gastric cancer patients, the perioperative FLOT regimen seemed to lead to a significant improvement in patients’ OS and PFS in comparison with ECF, DCF, and FOLFOX regimens. As such, the FLOT regimen could be considered as the optimal option for managing resectable gastric cancer patients.

scholarly journals Helicobacter pylori infection reduces likelihood of death from advanced cancer: A longitudinal analysis from the Japanese DAIKO prospective cohort study

2021 ◽  
Author(s):  
Satoshi S. Nishizuka ◽  
Masahiro Nakatochi ◽  
Yuka Koizumi ◽  
Asahi Hishida ◽  
Rieko Okada ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Survival Rate ◽  
Advanced Gastric Cancer ◽  
Cancer Patients ◽  
Cancer Incidence ◽  
Prospective Cohort ◽  
Factors Associated ◽  
Cancer Death Rate ◽  
Gastric Cancer Patients ◽  
Advanced Stage Cancer

AbstractBackgroundParadoxically, patients with advanced stomach cancer who are Helicobacter pylori-positive (HP+) have a higher survival rate than those who are HP-. This finding suggests that HP infection has beneficial effects for cancer treatment. Present study examines whether HP+ individuals have a lower likelihood of death from cancer than those who are HP-.Methods and findingsProspective cohort data (n = 4,982 subjects enrolled in the DAIKO study between 2008-2010) was used to assess whether anti-HP antibody status as a surrogate for past-present HP infection was associated with cancer incidence. The median age in the primary registry was 53 years-old (range 34-69 years-old). Over the 8-year observation period there were 234 (4.7%) cancer cases in the cohort and 88 (1.8%) all-cause deaths. Urine anti-HP antibody data was available for all but one participant (n = 4,981; 99.97%). The number of HP+ and HP- individuals was 1,826 (37%) and 3,156 (63%), respectively. Anti-HP antibody distribution per birth year revealed that earlier birth year was associated with higher HP+ rates. To remove confounding factors associated with birth year, a birth year-matched cohort (n = 3,376) was generated for subsequent analyses. All-cancer incidence was significantly higher in HP+ individuals than those who were HP- (p=0.00328), whereas there was no significant difference in the cancer death rate between HP+ and HP- individuals (p=0.888). Strikingly, we found that HP+ individuals who developed cancer had a better survival rate than would be expected based on cancer incidence. These results suggest that cancer patients who are HP+ may have a higher likelihood of survival than those who are HP-. Cox regression analysis for prognostic factors revealed that the hazards ratio of HP+ was 1.59-fold (95%CI 1.17-2.26) higher than HP- in all-cancer incidence.ConclusionsPotential systemic effects of HP+ status may contribute to reduced likelihood of death for patients with cancer.Data Availability StatementThe data cannot be shared publicly as data sharing is not permitted according to Japanese Government data protection policies. Requests for data analysis may be accepted anonymously and conditionally upon IRB approval from Iwate Medical University and Nagoya University Graduate School of Medicine.FundingThis study is supported by Grants-in-Aid for Scientific Research for Priority Areas of Cancer (No. 17015018); Grants-in-Aid for Innovative Areas (No. 221S0001); and the Japan Society for the Promotion of Science (JSPS) KAKENHI Grant (No. 19K09130 and No. 16H06277 [CoBiA]) from the Japanese Ministry of Education, Culture, Sports, Science and Technology (MEXT). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Competing interestsThe authors declare that no competing interests exist.Author summaryWhy was this study done?> Although HP infection is a major cause of gastric diseases including cancer, how HP infection affects prolonged survival of advanced gastric cancer patients is unknown.> Reports of studies carried out in different countries and regions revealed that advanced gastric cancer patients who are HP+ exhibited prolonged post-treatment survival, even though the genetic background of patients, HP strains, and cancer treatment procedures differed.> Since most advanced gastric cancer patients underwent gastrectomy, the favorable prognosis of HP+ patients after multidisciplinary treatment may be due to putative systematic mechanisms associated with HP infection.> If putative systemic mechanisms associated with HP infection reduce the likelihood of death due to cancer, the cancer survival rate in the HP+ population should be lower than that for the HP- population.What did the researchers do and find?> Using data from the DAIKO prospective cohort study in Nagoya, Japan, we analyzed the association between anti-HP antibody status, cumulative cancer incidence and all-cause and cancer-specific deaths.> The HP+ rate increased as birth year decreased. Thus, matching based on birth year between 1935 and 1975 was performed to correct for confounding factors associated with birth year.> Despite a significantly higher all-cancer incidence for HP+ individuals compared to those who were HP-, no difference in the all-cause and cancer death rate was observed between HP+ and HP- individuals.What do these findings mean?> HP+ individuals are less susceptible to death relative to their incidence of cancer.> Patients with advanced stage cancer who are HP+ may have a better treatment response/tolerance than those who are HP-.> Additional longitudinal analyses are warranted to evaluate the effect of HP+ status on prolonged survival of patients with advanced-stage cancer.

Artificial neural network and regression models for prediction of sewing thread consumption for multilayered fabric assembly at lockstitch 301 seam

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Md Vaseem Chavhan ◽  
M. Ramesh Naidu ◽  
Hayavadana Jamakhandi
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Regression Model ◽  
Regression Models ◽  
Network Models ◽  
Quadratic Regression ◽  
Neural Network Models ◽  
Content Type ◽  
Sewing Thread ◽  
Artificial Neural

Purpose This paper aims to propose the artificial neural network (ANN) and regression models for the estimation of the thread consumption at multilayered seam assembly stitched with lock stitch 301. Design/methodology/approach In the present study, the generalized regression and neural network models are developed by considering the fabric types: woven, nonwoven and multilayer combination thereof, with basic sewing parameters: sewing thread linear density, stitch density, needle count and fabric assembly thickness. The network with feed-forward backpropagation is considered to build the ANN, and the training function trainlm of MATLAB software is used to adjust weight and basic values according to the optimization of Levenberg Marquardt. The performance of networks measured in terms of the mean squared error and the layer output is set according to the sigmoid transfer function. Findings The proposed ANN and regression model are able to predict the thread consumption with more accuracy for multilayered seam assembly. The predictability of thread consumption from available geometrical models, regression models and industrial empirical techniques are compared with proposed linear regression, quadratic regression and neural network models. The proposed quadratic regression model showed a good correlation with practical thread consumption value and more accuracy in prediction with an overall 4.3% error, as compared to other techniques for given multilayer substrates. Further, the developed ANN network showed good accuracy in the prediction of thread consumption. Originality/value The estimation of thread consumed while stitching is the prerequisite of the garment industry for inventory management especially with the introduction of the costly high-performance sewing thread. In practice, different types of fabrics are stitched at multilayer combinations at different locations of the stitched product. The ANN and regression models are developed for multilayered seam assembly of woven and nonwoven fabric blend composition for better prediction of thread consumption.

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