Eurasian Journal of Medical and Natural Sciences 6-jild 5-son (2026) · 102–113-betlar

DEVELOPMENT OF A DIGITAL MODEL FOR PREDICTING MORBIDITY IN INFANTS DURING THE FIRST YEAR OF LIFE BASED ON NEONATAL DATA

Саидвалиева, Феруза

DOI: 10.5281/zenodo.20487653 · Manbada o'qish → · PDF (manba serverida)

Annotatsiya

Morbidity among infants during the first year of life remains one of the most significant medical and social challenges in modern pediatrics. Despite continuous improvements in neonatal care and reductions in infant mortality rates across many countries, the high prevalence of infectious, respiratory, neurological, and metabolic disorders in early childhood continues to substantially affect population health outcomes. Most pathological conditions developing during the first year of life are associated with risk factors already present in the neonatal period. Modern data analytics and machine learning technologies provide new opportunities for the early prediction of adverse health outcomes and the development of personalized preventive strategies.

Neonatal period; Digital health; Morbidity prediction; Machine learning; Risk stratification; Pediatrics; Perinatal risk factors.Неонатальный период; цифровое здравоохранение; прогнозирование заболеваемости; машинное обучение; стратификация риска; педиатрия; перинатальные факторы риска.

Metadata manbasi: jurnal OAI-PMH arxivi · Sindex to'liq matnni saqlamaydi, manbaga havola beradi.