scholarly journals Intelligent Algorithm-Based CT Imaging for Evaluation of Efficacy of Docetaxel Combined with Fluorouracil on Patients with Gastric Cancer

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Qianqian Chen ◽  
Xiaohong Wang ◽  
Rong Ding ◽  
Ziyao Wang
Keyword(s):  
Gastric Cancer ◽  
Decision Tree ◽  
Effective Rate ◽  
Ct Images ◽  
Control Group ◽  
Observation Group ◽  
Decision Tree Algorithm ◽  
Improvement Rate ◽  
Tree Algorithm ◽  
Segmentation Boundary

The study focused on the dual-source computed tomography (CT) images segmented by the decision tree algorithm, to explore the efficacy of docetaxel combined with fluorouracil therapy on gastric patients undergoing chemotherapy. In this study, 98 patients with gastric cancer who were treated in the hospital were selected as the research subjects. The decision tree algorithm was applied to segment dual-source CT images of gastric cancer patients. The decision tree is established according to the feature ring and the segmentation position. The machine inductively learns from the decision tree to extract the features of the CT image to obtain the optimal segmentation boundary. The observation group was treated with docetaxel combined with fluorouracil, and the control group was treated with docetaxel combined with tegafur gimeracil oteracil potassium capsules. The general data of the two groups of patients were comparable and not statistically significant ( P > 0.05 ). The two groups were compared for clinical efficacy, physical status, KPS score, improvement rate, and adverse drug reactions after treatment. The results showed that the improvement rate of physical fitness in the observation group was 38.78%, and the improvement rate in the control group was 18.37%. The total effective rate in the observation group was 42.85%, and the total effective rate in the control group was 36.73%. Obviously, the curative effect and improvement rate of physical fitness in the observation group were significantly better than those in the control group ( P < 0.05 ). In conclusion, the decision tree algorithm proposed in this study demonstrates superb capabilities in feature extraction of CT images. The machine inductively learns from the decision tree to extract the features of the CT image to obtain the optimal segmentation boundary. The effect of docetaxel combined with fluorouracil is better than that of docetaxel combined with tegafur gimeracil oteracil potassium capsules.

scholarly journals Apatinib, S-1 Combined with Paclitaxel Perfusion in the Treatment of Malignant Seroperitoneum of Gastric Cancer

2020 ◽  
Vol 4 (4) ◽  
Author(s):  
Zhiyu Wang ◽  
Dan Hong ◽  
Zhuoqi Zhang ◽  
Shenyong Su ◽  
Yan Shi ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Drug Resistance ◽  
Treatment Effect ◽  
Adverse Reactions ◽  
Total Effective Rate ◽  
Effective Rate ◽  
Good Prognosis ◽  
Control Group ◽  
Observation Group ◽  
And Control

Objective: To analyze the effect of apatinib, S-1 combined with paclitaxel perfusion on malignant seroperitoneum of gastric cancer. Methods: From December 2019 to May 2020, 172 patients with gastric cancer treated in our hospital were randomly divided into two groups: observation group and control group, 86 cases each. The control group adopted the method of S-1 combined with paclitaxel perfusion therapy in the treatment of malignant seroperitoneum of gastric cancer. The observation group was given oral apatinib on the basis of S-1 combined with paclitaxel perfusion therapy, and the dosage was 500 mg/d. Results: The total effective rate of treatment in the control group was 43.02%, while the total effective rate in the observation group was 69.77%; the drug resistance of the two groups of patients increased and the adverse reactions were low. Conclusion: Apatinib and S-1 combined with paclitaxel perfusion therapy can effectively improve the treatment effect, stabilize the patient's condition, increase the patient's drug resistance to adverse reactions, and have a good prognosis.

scholarly journals Classification of diabetes disease using decision tree algorithm (C4.5)

2021 ◽  
Vol 1869 (1) ◽  
pp. 012082
Author(s):  
B A C Permana ◽  
R Ahmad ◽  
H Bahtiar ◽  
A Sudianto ◽  
I Gunawan
Keyword(s):  
Decision Tree ◽  
Decision Tree Algorithm ◽  
Tree Algorithm

An Analysis of Factors Influencing Foreign Language Self-Efficacy Based on C5.0 Decision Tree Algorithm in Data Mining

2014 ◽  
Vol 538 ◽  
pp. 460-464
Author(s):  
Xue Li
Keyword(s):  
Data Mining ◽  
Decision Tree ◽  
Foreign Language ◽  
Language Learning ◽  
Learning Strategies ◽  
Self Efficacy ◽  
Foreign Language Learning ◽  
Decision Tree Algorithm ◽  
Tree Algorithm ◽  
C5.0 Decision Tree

Based on inter-correlation and permeability among disciplines, the author makes an attempt to apply the information science to cognitive linguistics to provide a new perspective for the study of foreign languages. The correlation between self-efficacy and such four factors as anxiety, learning strategies, motivation and learners’ past achievement is analyzed by means of data mining and the extent to which the above factors affect self-efficacy in language learning is explored in this paper. The paper employs the decision tree algorithm in SPSS Clementine. C5.0 decision tree algorithm is adopted to analyze data in the study. The results are elicited from the researches carried out in this paper. The increased anxiety is bound to weaken learners’ motivation over time. It is obvious that learners have low self-efficacy. It is very important to employ strategies in foreign language learning. Ignorance of using learning strategies may result in unplanned learning with unsatisfactory achievements in spite of more efforts involved. Self-efficacy in foreign language learning may be weakened accordingly. Learners’ past achievement is a reference dimension in measuring self-efficacy with weaker influence.

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