Prediction of Apnea of Prematurity in neonates using Support Vector Machines and Random Forests

Medicine & Life Sciences

• Support Vector Machine 72%
• Forests 70%
• Apnea 61%
• Newborn Infant 45%
• Machine Learning 33%
• Principal Component Analysis 31%
• Premature Infants 28%
• Respiration 24%
• Area Under Curve 24%
• Learning 21%
• Parturition 20%
• Delivery of Health Care 17%
• Child 12%

Business & Economics

• Support Vector Machine 100%
• Minorities 49%
• Prediction 48%
• Feature Extraction 45%
• Childbirth 41%
• Principal Component Analysis 40%
• Machine Learning 38%
• Learning Algorithm 35%
• Imbalance 27%
• Healthcare 19%

Engineering & Materials Science

• Random forests 62%
• Support vector machines 47%
• Supervised learning 31%
• Principal component analysis 27%
• Learning algorithms 24%
• Feature extraction 22%
• Machine learning 21%