Artificial intelligence models do not provide information about exactly how the predictions
are reached. This lack of transparency is a major drawback. Particularly in medical …

Abstract Convolutional Neural Network (CNN) is a prevalent topic in deep learning (DL)
research for their architectural advantages. CNN relies heavily on hyperparameter …

The objective of this systematic review is to analyze the application of machine learning for
the prediction of pregnancy complications through an extensive review of published …

Image classification is usually done using deep learning algorithms. Deep learning
architectures are set deterministically. The aim of this paper is to propose an evolutionary …

In accordance with the inability of various hair artefacts subjected to dermoscopic medical
images, undergoing illumination challenges that include chest-Xray featuring conditions of …

The last two years have taught us that we need to change the way we practice medicine.
Due to the COVID-19 pandemic, obstetrics and gynecology setting has changed …

The main cause of fetal death, of infant morbidity or mortality during childhood years is
attributed to congenital anomalies. They can be detected through a fetal morphology scan …

Differential evolution (DE) stands out as a straightforward yet remarkably powerful
evolutionary algorithm employed for real-world problem-solving purposes. In the DE …

Introduction Congenital anomalies are the most encountered cause of fetal death, infant
mortality and morbidity. 7.9 million infants are born with congenital anomalies yearly. Early …

Artificial intelligence (AI), along with its subfields of machine learning (ML) and deep
learning (DL), allows computational models to process and learn the data representations …