Predicting outcomes of pelvic exenteration using machine learning

Nursing and Health Professions

• Receiver Operating Characteristic 100%
• Patient 100%
• Pelvis Exenteration 75%
• Data Base 50%
• Procedures 50%
• Surgery 25%
• Complication 25%
• Length of Stay 25%
• Rectum Cancer 25%
• Colorectal Cancer 25%
• Computer 25%
• Electric Potential 25%
• Survival 25%
• Weight 25%
• Prediction 25%
• Support Vector Machine 25%
• Artificial Neural Network 25%

Computer Science

• Machine Learning 75%
• Artificial Neural Networks 50%
• Characteristic Curve 50%
• Database 50%
• Programming Environment 25%
• Performance Model 25%
• Network Performance 25%
• Logistic Regression 25%
• Artificial Neural Network 25%
• Prediction Accuracy 25%
• Support Vector Machine 25%
• Logistic Regression Model 25%
• Deep Learning 25%
• Computer 25%

Medicine and Dentistry

• Learning 100%
• Pelvic Exenteration 75%
• Logistic Regression Analysis 50%
• Aptitude 50%
• Complication 25%
• Surgery 25%
• Rectum Cancer 25%
• Accuracy 25%
• Survival 25%
• Prognosis 25%
• Predictive Modeling 25%