Predicting dementia with routine care EMR data

ZB Miled, K Haas, CM Black, RK Khandker… - Artificial Intelligence in …, 2020 - Elsevier
Our aim is to develop a machine learning (ML) model that can predict dementia in a general
patient population from multiple health care institutions one year and three years prior to the …

Charting everyday activities in later life: Study protocol of the mobility, activity, and social interactions study (MOASIS)

C Röcke, M Luo, P Bereuter, M Katana… - Frontiers in …, 2023 - frontiersin.org
Prominent theories of aging emphasize the importance of resource allocation processes as
a means to maintain functional ability, well-being and quality of life. Little is known about …

Best practices for Electronically Activated Recorder (EAR) research: A practical guide to coding and processing EAR data

DM Kaplan, KE Rentscher, M Lim, R Reyes… - Behavior Research …, 2020 - Springer
Since its introduction in 2001, the Electronically Activated Recorder (EAR) method has
become an established and broadly used tool for the naturalistic observation of daily social …

Sounds of healthy aging: Assessing everyday social and cognitive activity from ecologically sampled ambient audio data

B Demiray, M Luo, A Tejeda-Padron… - Personality and healthy …, 2020 - Springer
As proposed by the healthy aging model of the World Health Organization (2015),
participation in social and cognitive activities is important for healthy aging and for …

Automatic behavior assessment from uncontrolled everyday audio recordings by deep learning

D Schindler, S Spors, B Demiray, F Krüger - Sensors, 2022 - mdpi.com
The manual categorization of behavior from sensory observation data to facilitate further
analyses is a very expensive process. To overcome the inherent subjectivity of this process …

[HTML][HTML] Social reminiscence in older adults' everyday conversations: automated detection using natural language processing and machine learning

A Ferrario, B Demiray, K Yordanova, M Luo… - Journal of medical …, 2020 - jmir.org
Background Reminiscence is the act of thinking or talking about personal experiences that
occurred in the past. It is a central task of old age that is essential for healthy aging, and it …

[HTML][HTML] Predicting working memory in healthy older adults using real-life language and social context information: a machine learning approach

A Ferrario, M Luo, AJ Polsinelli, SA Moseley, MR Mehl… - JMIR aging, 2022 - aging.jmir.org
Background Language use and social interactions have demonstrated a close relationship
with cognitive measures. It is important to improve the understanding of language use and …

Understanding reminiscence and its negative functions in the everyday conversations of young adults: A machine learning approach

A Ferrario, B Demiray - Heliyon, 2024 - cell.com
Reminiscence is the act of recalling or telling others about relevant personal past
experiences. It is an important activity for all individuals, young and old alike. In fact …

With a little help from familiar interlocutors: Real-world language use in young and older adults

M Luo, R Debelak, G Schneider, M Martin… - Aging & Mental …, 2021 - Taylor & Francis
Objectives Functional psychologists are concerned with the performance of cognitive
activities in the real world in relation to cognitive changes in older age. Conversational …

Challenges providing ground truth for pervasive healthcare systems

K Yordanova - IEEE Pervasive Computing, 2019 - ieeexplore.ieee.org
The rapid growth of data collected for training models to detect activities and changes in
behavior and the adoption of wearables and smart devices are making the development of …