Microstructural asymmetry index (AI) as a function of age. by Junyu Guo (316439)

Age vs trust in AI for medical treatment. by Abdullah A. Alasmari (22566815)

“…This study presents a quantitative analysis of survey data from 335 participants to examine how demographic factors, age, gender, familiarity with AI, and frequency of technology use influence trust across a range of cognitive tasks. …”

Data_Sheet_1_Higher remnant cholesterol is associated with an increased risk of amnestic mild cognitive impairment: a community-based cross-sectional study.docx by Yating Ai (17331337)

Reality Drift: Navigating Culture, Cognition, and Policy in the AI Age by Dr. Samuel Wellington (22445725)

“…The framework builds on and extends earlier theories of hyperreality, surveillance capitalism, and cognitive offloading, providing policymakers, educators, and designers with actionable insights. Increasingly cited in think tank briefings and academic discourse, <i>Reality Drift</i> highlights systemic distortion, recursive feedback loops, and the erosion of shared meaning—making it a critical tool for governance in the AI age.…”

Ovarian disorders in aged <i>inhbaa</i>-/- mutant. by Cheng Zhao (2535307)

Data_Sheet_1_The Racial Disparities in the Epidemic of Metabolic Syndrome With Increased Age: A Study From 28,049 Chinese and American Adults.docx by Ruiying Zhang (3569693)

“…MetS was defined in accordance with the National Cholesterol Education Program Adult Treatment Panel III. A modified sliding-window-based algorithm was used to depict the trajectories of the prevalence of MetS with increased age. …”

Flow charts showing the performance for all the relevant pathologies (a) in all age groups, (b) 7–14 years, and (c) 2–6 years. by Prerana Agarwal (21781515)

Hazard function for the birth of a second child. by Jing Zhang (23775)

Subjects:

With increasing age, the FBA increased, then the NSA and the aMDFA increased, which finally led to a decreased mMDFA. by Yang Lu (59885)

Trust in AI for memory-related tasks. by Abdullah A. Alasmari (22566815)

“…This study presents a quantitative analysis of survey data from 335 participants to examine how demographic factors, age, gender, familiarity with AI, and frequency of technology use influence trust across a range of cognitive tasks. …”

AI familiarity levels among participants. by Abdullah A. Alasmari (22566815)

“…This study presents a quantitative analysis of survey data from 335 participants to examine how demographic factors, age, gender, familiarity with AI, and frequency of technology use influence trust across a range of cognitive tasks. …”

AUC for the Selected Age Range. by Hung-Lung Tsai (22189958)

“…<div><p>With an increasing aging population, the prevalence of chronic comorbidities is on the rise. …”

Supplementary file 1_The mushrooms on the menu (MOM) study: vitamin D mushrooms (UV-exposed) are a feasible and acceptable way to increase vitamin D intake in a residential aged care facility.docx by Celeste Ferraris (11279976)

“…Due to limited food sources, diet is frequently overlooked, yet mushrooms can raise vitamin D levels in deficient individuals similar to a supplement.</p>Objectives<p>Mushrooms on the Menu (MOM) was a 10-week prospective pre-post mixed method study that evaluated the feasibility of adding vitamin D mushrooms to the menu of a residential aged care facility.…”

All predictors of the aneurysmal subarachnoid hemorrhage (aSAH) prediction model in relation to the corresponding coefficients of these predictors in the acute ischemic stroke (AIS... by Jos P. Kanning (18706506)

Morphological alternations are not unique to APP^NL-F mice at 24 months age. by Katalin E. Sos (8910092)

<b>CABS Public Seminar Series 2023-24:</b><b>What is Artificial intelligence (AI) and what does it mean for older adults?</b> by Elena Moschini (18189794)

“…As AI is increasingly used in care environments, with promises of addressing systemic issues such as alleviating loneliness among residents, it is critical to consider its potential role in enhancing age-related bias and social inequalities in later life.   …”

Data_Sheet_1_NLRP3 Inflammasome-Dependent Increases in High Mobility Group Box 1 Involved in the Cognitive Dysfunction Caused by Tau-Overexpression.docx by Yan Zhao (58882)

Lack of hepcidin leads to progressive increases in serum nonheme iron and TSAT in male and female rats. by Shireen R. L. Flores (10994396)

Familiarity with AI vs trust in memory recall. by Abdullah A. Alasmari (22566815)

“…This study presents a quantitative analysis of survey data from 335 participants to examine how demographic factors, age, gender, familiarity with AI, and frequency of technology use influence trust across a range of cognitive tasks. …”

Trust levels in AI across cognitive tasks. by Abdullah A. Alasmari (22566815)

“…This study presents a quantitative analysis of survey data from 335 participants to examine how demographic factors, age, gender, familiarity with AI, and frequency of technology use influence trust across a range of cognitive tasks. …”