| Title: |
NUTRITION DETECTION DURING GESTATION PERIOD USING ML ALGORITHMS |
| Authors: |
Shreyas Vinayak Patil, Yash Harish Gupta |
| Source: |
International Journal of Latest Research in Engineering and Management, pp 01 - 06, Vol 07 - No. 04, 2023 |
| Abstract: |
The issue of low birth weight in infants is a significant concern in prenatal care, and it can have adverse effects on the newborn's health, sometimes leading to mortality. This problem contributes to high rates of child mortality worldwide. Artificial intelligence, particularly ML, offers potential solutions for predicting whether a fetus will be born small for its gestational age. Early detection of fetal developmental issues is critical, as timely intervention can increase gestation days and improve fetal weight at birth, reducing the risk of neonatal morbidity and mortality. This proposal aims to explore various machine learning methods for predicting small-for-gestational-age infants, emphasizing the importance of early detection and intervention to improve outcomes.
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| Keywords: |
Machine learning, gestation, Fetal weight, Cardiotocography |
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