Performance of a Short Version of the Everyday Cognition Scale (ECog-12) to Detect Cognitive Impairment.

Background: The Everyday Cognition (ECog) 12-item scale, a functional decline measurement, can distinguish dementia from cognitively unimpaired (CU). Limited data compare ECog-12 performance by raters (self vs. informant) and scoring systems (average numeric vs.

The ADNI Administrative Core: Ensuring ADNI's success and informing future AD clinical trials.

The Alzheimer's Disease Neuroimaging Initiative (ADNI) Administrative Core oversees and coordinates all ADNI activities, to ensure the success and maximize the impact of ADNI in advancing Alzheimer's disease (AD) research and clinical trials. It manages finances and develops policies for data sharing, publications using ADNI data, and access to ADNI biospecimens. The Core develops and executes pilot projects to guide future ADNI activities and identifies key innovative methods for inclusion in ADNI.

Remote olfactory assessment using the NIH Toolbox Odor Identification test and the brain health registry.

Background: Early identification of deficits in our ability to perceive odors is important as many normal (i.e., aging) and pathological (i.

Unsupervised Online Paired Associates Learning Task from the Cambridge Neuropsychological Test Automated Battery (CANTAB®) in the Brain Health Registry.

Background: Unsupervised online cognitive assessments have demonstrated promise as an efficient and scalable approach for evaluating cognition in aging, and Alzheimer's disease and related dementias.

Objectives: The aim of this study was to evaluate the feasibility, usability, and construct validity of the Paired Associates Learning task from the Cambridge Neuropsychological Test Automated Battery® in adults enrolled in the Brain Health Registry.

Design, Setting, Participants, Measurements: The Paired Associates Learning task was administered to Brain Health Registry participants in a remote, unsupervised, online setting.

An Approach for Generating Realistic Australian Synthetic Healthcare Data.

Healthcare data is a scarce resource and access is often cumbersome. While medical software development would benefit from real datasets, the privacy of the patients is held at a higher priority. Realistic synthetic healthcare data can fill this gap by providing a dataset for quality control while at the same time preserving the patient's anonymity and privacy.