Prediction of neural tube defect using support vector machine.

Keywords

Support vector machine, Training set, Test set, Artificial intelligence, Set (abstract data type)

References

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Cited by

• A spatial model to predict the incidence of neural tube defectsWilliam Phillips — 2012
• Support vector machines in water quality management.Kunwar P. Singh, Nikita Basant, Shikha Gupta — 2011
• Application of Genetic Algorithm-Support Vector Machine (GA-SVM) for Damage Identification of BridgeHanbing Liu, Yubo Jiao — 2011
• Predicting congenital heart defects: A comparison of three data mining methodsYanhong Luo, Zhi Li, Husheng Guo — 2017
• Complement factors and alpha‐fetoprotein as biomarkers for noninvasive prenatal diagnosis of neural tube defectsNaixuan Dong, Hui Gu, Dan Liu — 2020
• Predicting population health with machine learning: a scoping reviewJ. Morgenstern, Emmalin Buajitti, Meghan O’Neill — 2020
• Risk Assessment for Birth Defects in Offspring of Chinese Pregnant WomenPengfei Qu, Doudou Zhao, Mingxin Yan — 2022
• Research advancements in the Use of artificial intelligence for prenatal diagnosis of neural tube defectsMaryam Yeganegi, Mahsa Danaei, Sepideh Azizi — 2025
• Development of Hidden Markov Model to Predict Birth Defects: A Longitudinal Data StudyChenxi Kang, Shutong Zhang, Jing Cui — 2024
• Title A spatial model to predict the incidence of neural tube defects PermalinkLianfa Li, Jinfeng Wang, Jun Wu — 2013
• Overview of Predictive Modeling Approaches in Health Care Data MiningS. Soni — 2014

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