Publication | Open Access
Transporting an Artificial Intelligence Model to Predict Emergency Cesarean Delivery: Overcoming Challenges Posed by Interfacility Variation
12
Citations
11
References
2021
Year
Artificial IntelligenceEngineeringMachine LearningIntelligent DiagnosticsIntelligent SystemsBiomedical Artificial IntelligenceHealth Care FacilitiesPrimary CareArtificial Intelligence ModelData ScienceMedical Expert SystemAi HealthcareHealth Services ResearchCare DeliveryPrediction ModellingPredictive AnalyticsApplied Artificial IntelligenceInterfacility VariationNursingOvercoming ChallengesPatient SafetyPediatricsEmergency Medical ServiceMedicineClinical Decision Support SystemHealth InformaticsEmergency Medicine
Research using artificial intelligence (AI) in medicine is expected to significantly influence the practice of medicine and the delivery of health care in the near future. However, for successful deployment, the results must be transported across health care facilities. We present a cross-facilities application of an AI model that predicts the need for an emergency caesarean during birth. The transported model showed benefit; however, there can be challenges associated with interfacility variation in reporting practices.
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