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Models of logistic regression analysis, support vector machine, and back-propagation neural network based on serum tumor markers in colorectal cancer diagnosis
- Source :
- Genetics and molecular research : GMR. 15(2)
- Publication Year :
- 2016
-
Abstract
- We evaluated the application of three machine learning algorithms, including logistic regression, support vector machine and back-propagation neural network, for diagnosing congenital heart disease and colorectal cancer. By inspecting related serum tumor marker levels in colorectal cancer patients and healthy subjects, early diagnosis models for colorectal cancer were built using three machine learning algorithms to assess their corresponding diagnostic values. Except for serum alpha-fetoprotein, the levels of 11 other serum markers of patients in the colorectal cancer group were higher than those in the benign colorectal cancer group (P < 0.05). The results of logistic regression analysis indicted that individual detection of serum carcinoembryonic antigens, CA199, CA242, CA125, and CA153 and their combined detection was effective for diagnosing colorectal cancer. Combined detection had a better diagnostic effect with a sensitivity of 94.2% and specificity of 97.7%; combining serum carcinoembryonic antigens, CA199, CA242, CA125, and CA153, with the support vector machine diagnosis model and back-propagation, a neural network diagnosis model was built with diagnostic accuracies of 82 and 75%, sensitivities of 85 and 80%, and specificities of 80 and 70%, respectively. Colorectal cancer diagnosis models based on the three machine learning algorithms showed high diagnostic value and can help obtain evidence for the early diagnosis of colorectal cancer.
- Subjects :
- Oncology
Adult
Male
medicine.medical_specialty
Support Vector Machine
Colorectal cancer
Logistic regression
Back propagation neural network
Machine Learning
03 medical and health sciences
0302 clinical medicine
Text mining
Internal medicine
Genetics
medicine
Biomarkers, Tumor
Humans
Molecular Biology
Tumor marker
Aged
Artificial neural network
business.industry
Case-control study
Membrane Proteins
General Medicine
Middle Aged
medicine.disease
Support vector machine
Logistic Models
030220 oncology & carcinogenesis
CA-125 Antigen
Case-Control Studies
030211 gastroenterology & hepatology
Female
Neural Networks, Computer
business
Colorectal Neoplasms
Algorithms
Subjects
Details
- ISSN :
- 16765680
- Volume :
- 15
- Issue :
- 2
- Database :
- OpenAIRE
- Journal :
- Genetics and molecular research : GMR
- Accession number :
- edsair.doi.dedup.....dc8c8a6dec55463080270018d8726d04