Prediction of Intrauterine Growth Restriction and Preeclampsia Using Machine Learning-Based Algorithms: A Prospective Study

IA Vasilache, IS Scripcariu, B Doroftei, RL Bernad… - Diagnostics, 2024‏ - mdpi.com
(1) Background: Prenatal care providers face a continuous challenge in screening for
intrauterine growth restriction (IUGR) and preeclampsia (PE). In this study, we aimed to …

[HTML][HTML] Predicting intra-and postpartum hemorrhage through artificial intelligence

C Susanu, A Hărăbor, IA Vasilache, V Harabor… - Medicina, 2024‏ - mdpi.com
Background and Objectives: Intra/postpartum hemorrhage stands as a significant obstetric
emergency, ranking among the top five leading causes of maternal mortality. The aim of this …

Epigenetic alterations in preeclampsia: a focus on microRNA149 and tetrahydrofolate reductase gene polymorphisms in Egyptian women

DES Ellakwa, LA Rashed, AAA El-Mandoury… - Irish Journal of Medical …, 2024‏ - Springer
Background Preeclampsia (PE) poses a substantial risk to prenatal and maternal health.
Folic acid (FA) and methylenetetrahydrofolate reductase (MTHFR) play roles in DNA …

[HTML][HTML] Predicting unfavorable pregnancy outcomes in polycystic ovary syndrome (PCOS) patients using machine learning algorithms

R Mogos, L Gheorghe, A Carauleanu, IA Vasilache… - Medicina, 2024‏ - mdpi.com
Background and Objectives: Polycystic ovary syndrome (PCOS) is a complex disorder that
can negatively impact the obstetrical outcomes. The aim of this study was to determine the …

Machine Learning-Based Algorithms for Enhanced Prediction of Local Recurrence and Metastasis in Low Rectal Adenocarcinoma Using Imaging, Surgical, and …

CC Volovat, DV Scripcariu, D Boboc, SR Volovat… - Diagnostics, 2024‏ - mdpi.com
(1) Background: Numerous variables could influence the risk of rectal cancer recurrence or
metastasis, and machine learning (ML)-based algorithms can help us refine the risk …

[HTML][HTML] Predicting Adverse Neurodevelopmental Outcomes in Premature Neonates with Intrauterine Growth Restriction Using a Three-Layered Neural Network

A Bivoleanu, L Gheorghe, B Doroftei, IS Scripcariu… - Diagnostics, 2025‏ - mdpi.com
Background/Objectives: There is a constant need to improve the prediction of adverse
neurodevelopmental outcomes in growth-restricted neonates who were born prematurely …

FACTORES DE RIESGO ASOCIADOS EN EL DESARROLLO DE SÍNDROME HELLP EN GESTANTES ATENDIDAS EN EL INSTITUTO NACIONAL MATERNO …

S Rojas-Vargas - Revista Peruana de …, 2024‏ - … .inmp.gob.pe
Objetivo. Determinar los factores de riesgo en el desarrollo de Síndrome HELLP en
gestantes atendidas en el Instituto Nacional Materno Perinatal, 2018-2021. Materiales y …

[PDF][PDF] Machine Learning-Based Prediction of Intrauterine Growth Restriction and Preeclampsia: A Prospective Study

IS Scripcariu, IA Vasilache, I Pavaleanu, B Doroftei… - 2023‏ - preprints.org
(1) Background: The screening of preeclampsia (PE) and intrauterine growth restriction
(IUGR) represents a constant challenge for obstetricians. The aim of this study was to …

[PDF][PDF] Fresh vs. frozen embryo transfers in patients with KIR Bx haplotype: impact on reproductive outcomes.

R Maftei, B Doroftei, CC Vaduva… - European Review for …, 2023‏ - europeanreview.org
OBJECTIVE: A controversy persists over whether or not the type of embryo transfer (ET)
influences reproductive outcomes. This study aimed to evaluate the reproductive outcomes …

Role of artificial intelligence in the early detection of thrombocytopenia: An approach to improve health of pregnant women

S Thakur, VK Garg, AV Kumar - 2024 Sixth International …, 2024‏ - ieeexplore.ieee.org
Thrombocytopenia, which is a blood disorder with a 7–12% frequency of platelet
insufficiency, is frequently detected by obstetricians during normal surveillance during …