The reticular chemistry of metal–organic frameworks (MOFs) allows for the generation of an
almost boundless number of materials some of which can be a substitute for the traditionally …

Artificial intelligence (AI) is increasingly employed in health care fields such as oncology,
radiology, and dermatology. However, the use of AI in mental health care and …

Biological aging of human organ systems reflects the interplay of age, chronic disease,
lifestyle and genetic risk. Using longitudinal brain imaging and physiological phenotypes …

It is typically assumed that large networks of neurons exhibit a large repertoire of nonlinear
behaviours. Here we challenge this assumption by leveraging mathematical models derived …

How individual differences in brain network organization track behavioral variability is a
fundamental question in systems neuroscience. Recent work suggests that resting-state and …

Functional interactions between brain regions can be viewed as a network, enabling
neuroscientists to investigate brain function through network science. Here, we …

Convolutional neural networks (CNNs) constitute a widely used deep learning approach that
has frequently been applied to the problem of brain tumor diagnosis. Such techniques still …

Middle age has historically been an understudied period of life compared to older age, when
cognitive and brain health decline are most pronounced, but the scope for intervention may …

Identifying floods and producing flood susceptibility maps are crucial steps for decision-
makers to prevent and manage disasters. Plenty of studies have used machine learning …

Recent critical commentaries unfavorably compare deep learning (DL) with standard
machine learning (SML) approaches for brain imaging data analysis. However, their …