Deep learning has become a popular tool for medical image analysis, but the limited
availability of training data remains a major challenge, particularly in the medical field where …

Radiomics and genomics represent two of the most promising fields of cancer research,
designed to improve the risk stratification and disease management of patients with prostate …

Large populations worldwide have been deprived from nature experiences due to mass
quarantines and lockdowns during the COVID-19 pandemic, and face a looming mental …

Deep learning (DL) has been successfully applied to the diagnosis of ophthalmic diseases.
However, rare diseases are commonly neglected due to insufficient data. Here, we …

Deep learning models have been used in several domains, however, adjusting is still
required to be applied in sensitive areas such as medical imaging. As the use of technology …

The recent rise of deep learning (DL) and its promising capabilities in capturing non-explicit
detail from large datasets have attracted substantial research attention in the field of medical …

The early prediction of Alzheimer's disease (AD) can be vital for the endurance of patients
and establishes as an accommodating and facilitative factor for specialists. The proposed …

The mere copresence of another person synchronizes physiological signals, but no study
has systematically investigated the effects of the type of emotional state and the type of …

The detection of brain tumors using magnetic resonance imaging is currently one of the
biggest challenges in artificial intelligence and medical engineering. It is important to identify …

Social robots represent a valid opportunity to manage the diagnosis, treatment, care, and
support of older people with dementia. The aim of this study is to validate the Mini-Mental …