Nomogram to Early Screen Multiparous Women for Preterm Birth in a Cohort Study

Preterm Birth (PTB) can negatively affect the health of mothers as well infants. Prediction this gynecological complication remains difficult especially in Middle and Low-Income countries because limited access to specific tests data collection scarcity. Machine learning methods have been used predict PTB but low prevalence pregnancy led rather prediction values. The objective study was produce a nomogram based on improved for using up sampling lasso penalized regression. We from cohort Northern Lebanon 922 multiparous presenting 8%. analyzed personal, demographic, indicators available group women. Positive Predictive Value reached around 88%. regression coefficients 6 selected variables (Pre-hemorrhage, Social status, Residence, Age, BMI, Weight gain) were create screen women risk. readily reasonably predicted most at risk physicians use tool high spontaneous preterm birth improve medical surveillance that reduce incidence.