Progress in dementia research has been limited, with substantial gaps in our knowledge of
targets for prevention, mechanisms for disease progression, and disease-modifying …

Introduction Artificial intelligence (AI) and neuroimaging offer new opportunities for
diagnosis and prognosis of dementia. Methods We systematically reviewed studies …

Dementia is a chronic and degenerative condition affecting millions globally. The care of
patients with dementia presents an ever-continuing challenge to healthcare systems in the …

Artificial intelligence (AI) approaches pose a great opportunity for individualized, pre-
symptomatic disease diagnosis which plays a key role in the context of personalized …

INTRODUCTION The use of applied modeling in dementia risk prediction, diagnosis, and
prognostics will have substantial public health benefits, particularly as “deep phenotyping” …

With the increase in large multimodal cohorts and high‐throughput technologies, the
potential for discovering novel biomarkers is no longer limited by data set size. Artificial …

Introduction Advanced machine learning methods might help to identify dementia risk from
neuroimaging, but their accuracy to date is unclear. Methods We systematically reviewed the …

Objective Alzheimer disease (AD) is the most common cause of dementia, a syndrome
characterized by cognitive impairment severe enough to interfere with activities of daily life …

Deep learning, a state-of-the-art machine learning approach, has shown outstanding
performance over traditional machine learning in identifying intricate structures in complex …

Aim: Research suggests that Alzheimer's disease (AD) is heterogeneous with numerous
subtypes. Through a proprietary interactive ML system, several underlying biological …