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Validation Studies
100%
Survey Data
100%
Shift Worker
100%
Algorithm Development
100%
Algorithm Validation
100%
Machine Learning Algorithms
66%
Sleep Duration
66%
Bedroom
66%
Shift Work Sleep Disorder
66%
Fitbit
66%
Cognitive Behavioral Therapy for Insomnia (CBT-I)
66%
Prediction Model
33%
Patient-specific
33%
Intensive Care Unit
33%
First Week
33%
Hierarchical Clustering
33%
Japan
33%
Performance Difference
33%
Popular
33%
Circadian Rhythm
33%
Behavioral Characteristics
33%
Web-based
33%
Proper Management
33%
Behavioral Patterns
33%
Sleep Quality
33%
Specific Strategies
33%
Shift Pattern
33%
Random Forest
33%
Shift Work
33%
Physiological Features
33%
Trustworthiness
33%
Day Shift
33%
App-based
33%
Synthetic Minority Oversampling Technique (SMOTE)
33%
Feature Importance Analysis
33%
Permutation Importance
33%
Area Under the Precision-Recall Curve
33%
Smartphone Use
33%
Shapley Additive Explanations
33%
Wearable Data
33%
Work Shift
33%
Light Gradient Boosting Machine
33%
CatBoost
33%
Modern Economy
33%
Nap Duration
33%
Balancing Strategy
33%
Random Undersampling
33%
Sleep Environment
33%
Data Balancing
33%
Average Brightness
33%
Computer Science
Machine Learning Algorithm
100%
Algorithm Development
100%
Sleep Duration
100%
Performance Difference
50%
Prediction Model
50%
Random Decision Forest
50%
Hierarchical Clustering
50%
Gradient Boosting
50%
Behavioral Feature
50%
Behavioral Pattern
50%
SHapley Additive exPlanation
50%
Catboost
50%
Neuroscience
Sleep Disorder
100%
Cognitive Behavioral Therapy
100%
Machine Learning Algorithm
100%
Sleep Time
100%
Behavior (Neuroscience)
50%
Circadian Rhythm
50%
Sleep Quality
50%
Prediction Model
50%
Engineering
Machine Learning Algorithm
100%
Oversampling
100%
Patient Specific
50%
Japan
50%
Intensive Care Unit
50%
Raw Data
50%
Hierarchical Clustering
50%
Random Forest
50%
Light Gradient Boosting Machine
50%
Psychology
Validation Study
100%
Sleep Disorder
100%
Learning Algorithm
100%
Cognitive Behavioral Therapy
100%
Circadian Rhythm
50%