Year: 2025
Type: article
Abstract: Preterm birth (PTB), defined as childbirth occurring before 37 weeks of gestation, is a major global health issue and the primary cause of mortality in children under five. Early detection of PTB is crucial to initiate timely interventions and prevent complications such as low birth weight and long-term developmental issues. However, conventional diagnostic methods, including ultrasounds and biochemical tests, often face limitations in terms of accessibility and accuracy. With the growing availability of clinical and physiological data during pregnancy, machine learning offers a promising alternative for early and cost-effective PTB prediction.
Authors: Setty Maheswari, Priya R, Sanjana Shetty, Allwin Raja, Vijayakumari G -
Institution: CMR University
Language: English
Subfield: Health Information Management
Field: Health Professions
Domain: Health Sciences
Open Access status: hybrid
OpenAlex ID: W4409617258