Objective Pre‐eclampsia (PE) is a serious complication of pregnancy associated with
maternal and fetal morbidity and mortality. As current prediction models have limitations and …

Objective Pre-eclampsia (PE) is a serious complication of pregnancy associated with
maternal and fetal morbidity and mortality. As current prediction models have limitations and …

Explainability is crucial in domains where system decisions have significant implications for
human trust in black-box models. Lack of understanding regarding how these decisions are …

Abstract The development of Artificial Intelligence (AI) technology is used to minimize the
risk of maternal disorders during pregnancy. Maternal health needs to be monitored so as …

While preeclampsia is the leading cause of maternal death in Guayas province (Ecuador),
its causes have not yet been studied in depth. The objective of this research is to build a …

Prediction of women at high risk of preeclampsia is important for prevention and increased
surveillance of the disease. Current prediction models need improvement, particularly with …

Objectives To evaluate the performance of an artificial intelligence (AI) and machine
learning (ML) model for first‐trimester screening for pre‐eclampsia in a large Asian …

Background Preeclampsia (PE) presence could lead to hemodynamic changes. Previous
research suggested that morphological parameters based on photoplethysmographic pulse …

It's no secret that security systems rely heavily on image processing because of its versatility.
Two-dimensional visuals, intricate algorithms, and instantaneous decision-making are all …

Abstract Machine learning is an area that helps to predict outcomes more accurately. It was
utilized in different domains such as banking, healthcare, education, etc. Among all the …