| Autor: |
Sahana, L. S., Thilaiarasu |
| Předmět: |
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| Zdroj: |
AIP Conference Proceedings; 2024, Vol. 2742 Issue 1, p1-8, 8p |
| Abstrakt: |
In both the mother and the fetus, proper fetal weight measurement is beneficial. Pregnant women with low birth weight (LBW) or high birth weight (HBW) have an increased risk of perinatal mortality, as well as additional difficulties and long-term health problems. Having a baby with a low fetal weight at birth is one of the most serious concerns in maternity care and can lead to the death of the baby. The high rates of infant mortality around the world are due to this disorder. It is possible to forecast fetal health risks with artificial intelligence approaches, especially those based on machine learning (ML). The health of a pregnant woman and her baby premature fetuses can be predicted using several machine learning (ML) techniques, as part of this paper's research. Fetal growth abnormalities can be detected early if the gestation period can be extended through timely intervention. Infant mortality and morbidity will be reduced as a result of an increase in birth weight. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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