Pregledni rad
https://doi.org/10.26332/dabq9171
The Role of Artificial Intelligence from Preconception to Postpartum
Terezija Berlančić
; Faculty of Medicine Osijek, J. J Strossmayer University in Osijek, Croatia; Department of Gynecology and Obstetrics, General County Hospital Našice, Croatia; Faculty of Economics and Business in Osijek, J. J. Strossmayer University in Osijek, Croatia
Blaženka Miškić
; Faculty of Dental Medicine and Health Osijek, J. J Strossmayer University in Osijek; General Hospital "Dr. Josip Benčevic" Slavonski Brod
Karla Miškić
; Faculty of Dental Medicine and Health Osijek, J. J Strossmayer University in Osijek; Dental Office dr. Karla Miškić
Rajko Fureš
orcid.org/0000-0001-6494-0972
; Faculty of Dental Medicine and Health Osijek, J. J Strossmayer University in Osijek; Department of Gynecology and Obstetrics, Zabok General Hospital and Croatian Veterans Hospital
Ivana Erceg Ivkošić
orcid.org/0000-0001-6125-1864
; Faculty of Dental Medicine and Health Osijek, J. J Strossmayer University in Osijek; St. Catherine Specialty Hospital
Vesna Ćosić
orcid.org/0000-0002-9556-8170
; Faculty of Dental Medicine and Health Osijek, J. J. Strossmayer University in Osijek, Croatia; Ćosić Polyclinic, Slavonski Brod, Croatia
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* Dopisni autor.
Sažetak
Artificial intelligence (AI) is increasingly applied across obstetrics, supporting care from preconception to postpartum. By using large databases, including imaging, genomics, laboratory profiles, and electronic health records, machine learning and deep learning models can generate insights that surpass traditional methods, and enable more personalized maternal–fetal care. In the preconception and fertility stage, AI is a tool used in infertility diagnostics, sperm, oocyte and embryo selection in assisted reproductive technology, improving success rates and efficiency. During pregnancy predictive algorithms can help with monitoring fetal biometry and fetal growth rate. AI also contributes to intrapartum monitoring by providing more consistent interpretation of cardiotocography and contraction patterns, potentially reducing unnecessary interventions and improving neonatal outcomes. Similarly to ultrasound during pregnancy AI can be used to analyze intrapartum ultrasound monitoring and help in diagnosing dystocia which could lead to fewer cesarian sections and further complications. Intrapartum and during early postpartum period AI can be used to evaluate and predict possible postpartum hemorrhage. Despite significant progress, challenges remain regarding data quality, algorithmic bias, interpretability, and integration into everyday practice. However, with further research and use in everyday clinical practice AI has a possibility to become an irreplaceable tool to every practitioner.
Ključne riječi
artificial intelligence; clinical decision support systems; machine learning; obstetrics and gynecology
Hrčak ID:
342750
URI
Datum izdavanja:
29.12.2025.
Posjeta: 243 *