Promoting Natural Birth Amid the Rising Trend of Cesarean Deliveries with the Aid of Artificial Intelligence
Abstract
The global rise in cesarean deliveries has become a major public health concern, with many procedures performed without clear medical necessity. While cesarean section (CS) remains a life-saving intervention for high-risk pregnancies, its overuse is linked to increased maternal and neonatal complications. Consequently, promoting safe natural birth has gained renewed emphasis, supported by advancements in medical technologies—particularly artificial intelligence (AI). This paper explores the role of AI in promoting natural childbirth through predictive, personalized, and real-time approaches. AI algorithms can analyse vast clinical datasets to predict labor risks, personalize care plans, and support real-time decision-making during delivery. Furthermore, AI-driven monitoring systems and educational tools empower both clinicians and expectant mothers, reducing elective and repeat cesarean procedures. Emerging evidence indicates that AI applications in obstetrics, such as predictive models for vaginal birth after cesarean (VBAC) and continuous fetal monitoring, enhance maternal and neonatal outcomes while improving clinical confidence in natural birth management. Despite its potential, AI implementation faces challenges related to data quality, system integration, bias, ethical concerns, and cost. Ensuring transparency, equity, and rigorous clinical validation remains essential to maintain trust and safety. In conclusion, AI represents a transformative opportunity to complement obstetric expertise, reduce unnecessary surgical interventions, and promote safer, more natural childbirth experiences. The future of obstetric care depends on harmonizing technological innovation with human compassion, ensuring that AI enhances—not replaces—the vital role of clinicians in supporting women through childbirth.
Fields of Study & Subjects
Maternal and Perinatal Health Interventions
Artificial Intelligence in Healthcare and Education
Artificial Intelligence in Healthcare
Publication details
- Journal / source
- World Journal of Biology Pharmacy and Health Sciences
- Volume
- 25
- Issue
- 2
- Pages
- 222–228
- Publication date
- 17 February 2026
- Language
- EN