Clinical Precision of Artificial Intelligence-Enhanced Cardiotocography Analysis in the Reduction of Intrapartum Neonatal Encephalopathy

International Journal of Obstetrics and Gynecology | Vol. 14, No. 9, September 2026 | pp. 687–698

DOI: 10.46882/2026/IJOG/000538

Original Research Article

Title: Clinical Precision of Artificial Intelligence-Enhanced Cardiotocography Analysis in the Reduction of Intrapartum Neonatal Encephalopathy

Names of Authors: Chinedu O. Okafor¹, Fatima B. Aliyu²

Authors’ Affiliations:
¹ Department of Maternal-Fetal Medicine, University of Nigeria Teaching Hospital, Enugu, Nigeria
² Department of Obstetrics and Gynecology, Aminu Kano Teaching Hospital, Kano, Nigeria

Abstract:
Intrapartum fetal monitoring relies heavily on Cardiotocography (CTG), which is limited by substantial inter-observer variation and high false-positive rates for fetal distress. This prospective multi-center intervention trial evaluated the clinical utility of a real-time, artificial intelligence (AI)-driven automated CTG interpretation platform in lowering the rates of neonatal hypoxic-ischemic encephalopathy (HIE) and emergency operative deliveries. A cohort of 3,200 laboring women at term was assigned to either the AI-guided monitoring cohort (real-time automated alerts for abnormal patterns; n = 1,600) or the control cohort (standard clinical visual analysis; n = 1,600). The primary outcome measured was the incidence of confirmed neonatal HIE. Results demonstrated a significant reduction in the incidence of neonatal HIE in the AI-guided group compared to the control group (0.12% vs. 0.56%; Relative Risk [RR] = 0.21; 95% Confidence Interval [CI], 0.06 to 0.78; p = 0.012). Crucially, the rate of emergency cesarean deliveries performed for suspected fetal distress was significantly lower in the AI cohort (8.4% vs. 13.6%, p < 0.001), reflecting a drop in false-positive visual alerts. Mean neonatal umbilical artery pH at delivery was higher in the intervention arm (7.26 ± 0.04 vs. 7.21 ± 0.06, p = 0.004). Continuous AI-enhanced cardiotocography evaluation provides an objective decision-support layer during labor, significantly improving neonatal neurological safety margins while concurrently mitigating avoidable surgical interventions.

Keywords: Cardiotocography; Artificial Intelligence; Neonatal Encephalopathy; Intrapartum Monitoring; Fetal Distress; Cesarean Section.

Manuscript Timeline: Received: July 20, 2026; Revised: August 18, 2026; Accepted: September 02, 2026; Published: September 05, 2026.

Citation: Okafor CO, Aliyu FB. Clinical Precision of Artificial Intelligence-Enhanced Cardiotocography Analysis in the Reduction of Intrapartum Neonatal Encephalopathy. International Journal of Obstetrics and Gynecology. 2026; 14(9): 687–698.

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