Feature selection is a preprocessing technique that identifies the key features of a given
problem. It has traditionally been applied in a wide range of problems that include biological …

Neuroimaging-based single subject prediction of brain disorders has gained increasing
attention in recent years. Using a variety of neuroimaging modalities such as structural …

Abstract Machine learning is increasingly being applied to neuroimaging data. However,
most machine learning algorithms have not been designed to accommodate neuroimaging …

Rationale and Objectives The automated segmentation of organs and tissues throughout the
body using computed tomography and magnetic resonance imaging has been rapidly …

Purpose To perform a systematic review on the research on the application of artificial
intelligence (AI) to imaging published in Italy and identify its fields of application, methods …

Alzheimer's disease is basically a neurodegenerative disease that is impossible to fully be
cured. It is one kind of dementia that occurs along with aging. It not only damages human …

Background Advances in DNA sequencing revolutionized plant genomics and significantly
contributed to the study of genetic diversity. However, predicting phenotypes from genomic …

Radiomics is a novel concept that relies on obtaining image data from examinations such as
computed tomography (CT), magnetic resonance imaging (MRI), or positron emission …

Context. The explosion of data in recent years has generated an increasing need for new
analysis techniques in order to extract knowledge from massive data-sets. Machine learning …

Abstract The Coronavirus disease 2019 (COVID-19) pandemic has officially spread all over
the world since the beginning of 2020. Although huge efforts are addressed by scientists to …