Predicting Post-Operative Complications with Wearables: A Case Study with Patients Undergoing Pancreatic Surgery

Keyphrases

• Postoperative Complications 100%
• Feature Engineering 100%
• Pancreatic Surgery 100%
• Time Series Data 60%
• High-level Features 60%
• Wearable Sensors 40%
• Engineering Approach 40%
• Wearable Data 40%
• Clinical Characteristics 20%
• Patient Care 20%
• Clinical Setting 20%
• Clinical Practice 20%
• Severe Complications 20%
• Hospital Readmission 20%
• Heart Rate 20%
• Non-invasive Monitoring 20%
• Clinical Prediction Model 20%
• Patient Monitoring 20%
• Missing Data 20%
• Surgical Patients 20%
• Area under the Receiver Operating Characteristic (AUROC) 20%
• Machine Learning Models 20%
• Resilient 20%
• Integrated Features 20%
• Linear Support Vector Machine 20%
• Postoperative Readmission 20%
• Wearable Devices 20%
• K-nearest 20%
• Fitbit 20%
• Wristband 20%
• Engineering Framework 20%
• Art Features 20%
• Singular Spectrum Analysis 20%
• Multi-level Features 20%
• Rule-based Model 20%
• Effective Characteristics 20%
• Predictive Model 20%
• Healthcare Providers 20%
• Real-world Clinical Practice 20%

Computer Science

• Case Study 100%
• Feature Engineering 100%
• Time Series Data 60%
• Collected Data 20%
• Healthcare Provider 20%
• Support Vector Machine 20%
• Predictive Model 20%
• Wearable Device 20%
• Neighbor Method 20%
• Accurate Predictive Model 20%
• Singular Spectrum 20%
• Machine Learning Model 20%