No abstract

Background: Maternal anemia is frequently associated with premature delivery, reduced neonatal weight, infant iron deficiency, neonatal death, and low Apgar scores at 1 min. It is also suspected to reduce the oxygen supply to the growing fetus, leading to the redistribution of fetal blood flow. This study aims to evaluate the effect of the different types of iron medications given to anemic patients on fetal Doppler indices namely umbilical artery and middle cerebral artery in the late second trimester of pregnancy. Materials and Methods: This cohort prospective study. This study conducted at department of obstetrics and gynecology at Tanta university hospital. Participants consisted of 90 pregnant women during their gestational age (20-28 weeks) they were attended or admitted to obstetric unit.divided into 3 groups. Lactoferrin group included 30 cases received 250 mg lactoferrin capsules once daily for 4 weeks. Iron amino acid chelated group included 30 cases received ferrous bis – glycine chelate (FeBC) 15 mg/day for 4 weeks. Ferrous fumarate group included 30 cases received 350 mg dried ferrous fumarate capsules once daily for 4 weeks. Pre-and post-treatment Doppler measurement of umbilical artery and middle cerebral artery parameter compared 4 weeks after the start of treatment for patients whose anemia successfully treated. Results: Post hoc analysis of maternal serum hemoglobin of the studied groups show insignificant different between the groups. Pre- and Post-treatment follow-up of resistance index (RI) of the studied groups, Pre- and Post-treatment follow-up of pulsatility index (PI) of the studied groups, Post hoc analysis of pulsatility index (PI) of the studied groups and Post hoc analysis of resistance index (RI) of the studied groups show insignificant different between groups. Conclusion: Based on our results, it can be concluded that cerebral vasodilatation due to severe maternal anemia is a reversible condition that can be corrected through the prompt treatment of anemia. Additionally, the three therapeutics tested in the current study showed a comparable effect in treating maternal anemia, with subsequent improvement of doppler indices.

No abstract

Support vector regression (SVR) is one of the supervised machine learning algorithms that can be exploited for prediction issues. The main enhancement issue of SVR is attempting to select a reliable parameter to assure the high performance of SVR. In this paper, the intelligent approach is based on integrating the enhanced particle swarm optimization PSO with the SVR to achieve the proper SVR parameters that are used to improve SVR performance. The enhanced PSO is performed by implementing parallelized linear time-variant acceleration coefficients (TVAC) and inertia weight (IW) of PSO, called PLTVACIW-PSO. The proposed approach is evaluated by performing the experimental comparisons of the proposed algorithm with eleven different algorithms. These comparisons are performed by applying the proposed algorithm and these algorithms to 21 different datasets varying in their scales.

No abstract