Alzheimer's Disease (AD) is one of the leading causes of death in developed countries.
From a research point of view, impressive results have been reported using computer-aided …

Neuroimaging has made it possible to measure pathological brain changes associated with
Alzheimer's disease (AD) in vivo. Over the past decade, these measures have been …

Mindboggle (http://mindboggle. info) is an open source brain morphometry platform that
takes in preprocessed T1-weighted MRI data and outputs volume, surface, and tabular data …

We initiated the systematic profiling of the dorsolateral prefrontal cortex obtained from a
subset of autopsied individuals enrolled in the Religious Orders Study (ROS) or the Rush …

A large number of papers have introduced novel machine learning and feature extraction
methods for automatic classification of Alzheimer's disease (AD). However, while the vast …

Improved risk stratification and prognosis prediction in sepsis is a critical unmet need.
Clinical severity scores and available assays such as blood lactate reflect global illness …

Alzheimer's disease (AD) is a remarkable challenge for healthcare in the 21st century. Since
2017, deep learning models with transfer learning approaches have been gaining …

Most scientific research is conducted by small teams of investigators who together formulate
hypotheses, collect data, conduct analyses, and report novel findings. These teams operate …

Alzheimer's and related diseases are significant health issues of this era. The
interdisciplinary use of deep learning in this field has shown great promise and gathered …

Big data analytics (BDA) is of paramount importance in healthcare aspects such as patient
diagnostics, fast epidemic recognition, and improvement of patient management. The …