Reliability of machine learning to diagnose pediatric obstructive sleep apnea: Systematic review and meta-analysis

Keyphrases

• Meta-analysis 100%
• Systematic Meta-analysis 100%
• Machine Learning 100%
• Pediatric Obstructive Sleep Apnea 100%
• Publication Bias 50%
• Apnea-hypopnea Index 50%
• Summary Receiver Operating Characteristic 50%
• Healthcare Professionals 25%
• True Positive 25%
• Receiver Operating Characteristic Analysis 25%
• Nineteen 25%
• Confidence Level 25%
• Clinical Practice 25%
• Polysomnography 25%
• Web of Science 25%
• True Negative 25%
• Machine Learning Techniques 25%
• Electronic Search 25%
• Scopus 25%
• Random Effects Model 25%
• Diagnostic Performance 25%
• Machine Learning Approach 25%
• Pediatric Sleep 25%
• True-false 25%
• I(2) 25%
• Diagnostic Standards 25%
• High Heterogeneity 25%
• False-positive Cases 25%
• Sleep Study 25%
• Synthesis Methods 25%
• Minor Effect 25%
• Appraisal Methods 25%
• Obstructive Sleep Apnea Severity 25%
• Applied Machine Learning 25%
• Bias Correction 25%
• Severity Criteria 25%
• Bibliographic References 25%

Medicine and Dentistry

• Pediatrics 100%
• Meta-Analysis 100%
• Systematic Review 100%
• Obstructive Sleep Apnea 100%
• Apnea 40%
• Hypopnea 40%
• Sensitivity and Specificity 20%
• False Negative Result 20%
• False Positive Result 20%
• Polysomnography 20%
• Random Effects Model 20%
• Diagnostic Performance 20%
• Sleep Studies 20%
• Health Care Personnel 20%

Agricultural and Biological Sciences

• Meta-Analysis 100%
• Systematic Review 100%
• Obstructive Sleep Apnea 100%
• Learning System 100%
• Machine Learning 100%
• Spider Web 20%