Combining genetic risk score with artificial neural network to predict the efficacy of folic acid therapy to hyperhomocysteinemia

• Published in: Scientific reports Vol. 11; no. 1; pp. 21430 - 10
• Main Authors: Chen, Xiaorui, Huang, Xiaowen, Jie, Diao, Zheng, Caifang, Wang, Xiliang, Zhang, Bowen, Shao, Weihao, Wang, Gaili, Zhang, Weidong
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 02.11.2021; Nature Publishing Group; Nature Portfolio
• Subjects: 631/114; 631/208; 692/308; 692/4017; 692/499; 692/53; 692/700; Acids; Aged; Algorithms; Environmental factors; Female; Folic acid; Folic Acid - therapeutic use; Genetic Markers; Genetic Predisposition to Disease; Humanities and Social Sciences; Humans; Hyperhomocysteinemia; Hyperhomocysteinemia - drug therapy; Hyperhomocysteinemia - genetics; Hyperhomocysteinemia - pathology; Male; multidisciplinary; Nervous system; Neural networks; Neural Networks, Computer; Prospective Studies; Risk Factors; Science; Science (multidisciplinary); Treatment Outcome; Vitamin B

Artificial neural network (ANN) is the main tool to dig data and was inspired by the human brain and nervous system. Several studies clarified its application in medicine. However, none has applied ANN to predict the efficacy of folic acid treatment to Hyperhomocysteinemia (HHcy). The efficacy has b...