Machine learning methods in predicting Down Syndrome

Yuqi Yan; Yihan Wang; Yimin Yu

doi:10.1117/12.2628500

7 March 2022 Machine learning methods in predicting Down Syndrome

Yuqi Yan, Yihan Wang, Yimin Yu

Proceedings Volume 12167, Third International Conference on Electronics and Communication; Network and Computer Technology (ECNCT 2021); 1216732 (2022) https://doi.org/10.1117/12.2628500
Event: 2021 Third International Conference on Electronics and Communication, Network and Computer Technology, 2021, Harbin, China

Abstract

Part causes down syndrome or all the third copy of chromosome 21, has been discovered for over a hundred years. Although many studies have been carried in this field to find out how to cure the patients or animals, no researchers can fully treat this disease. Thus, this research manages to analyze the expression level of the proteins encoded by the genes in mice with down syndrome by using the binary logistic regression method. The consequence shows that two significant proteins are affected most -- ITSN1_N and BRAF_N. Behind this, the predicted data are carried by 10-folds crossvalidation, then find out the result has high accuracy. Moreover, the data are randomly divided into 20%, 40%, 60%, and 80% to test the relationship between data quantity and accuracy, and it shows that the more data amount, the more precise it can be.

Citation Download Citation

Yuqi Yan, Yihan Wang, and Yimin Yu "Machine learning methods in predicting Down Syndrome", Proc. SPIE 12167, Third International Conference on Electronics and Communication; Network and Computer Technology (ECNCT 2021), 1216732 (7 March 2022); https://doi.org/10.1117/12.2628500

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