AIMC Topic: Dementia

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Beyond Phecodes: leveraging PheMAP to identify patients lacking diagnosis codes in electronic health records.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Diagnosis codes documented in electronic health records (EHR) are often relied upon to clinically phenotype patients for biomedical research. However, these diagnoses can be incomplete and inaccurate, leading to false negatives when search...

Translational approach for dementia subtype classification using convolutional neural network based on EEG connectome dynamics.

Scientific reports
Dementia spectrum disorders, characterized by progressive cognitive decline, pose a significant global health burden. Early screening and diagnosis are essential for timely and accurate treatment, improving patient outcomes and quality of life. This ...

Identifying Key Factors Associated with Assistive Technology Availability for Dementia Care Using Machine Learning.

Studies in health technology and informatics
This study explores the factors influencing the availability of assistive technology for people with dementia through the application of machine learning. The analysis identified key factors, including carer support, protective legislation, and acces...

A Medical Decision Support System for Automatic Treatment Plan Generation Using Machine Learning Algorithms.

Studies in health technology and informatics
Due to demographic change, health economics is increasingly focused on the quality of life in advanced age and the associated cost aspects. Dementia is one of the key issues in this area and its efficient treatment will become increasingly relevant i...

Advancing Remote Monitoring for Patients With Alzheimer Disease and Related Dementias: Systematic Review.

JMIR aging
BACKGROUND: Using remote monitoring technology in the context of Alzheimer disease (AD) care presents exciting new opportunities to lessen caregiver stress and improve patient care quality. The application of wearables, environmental sensors, and sma...

Development and validation of a novel predictive model for dementia risk in middle-aged and elderly depression individuals: a large and longitudinal machine learning cohort study.

Alzheimer's research & therapy
BACKGROUND: Depression serves as a prodromal symptom of dementia, and individuals with depression exhibit a significantly higher risk of developing dementia. The aim of this study is to develop and validate a novel dementia risk prediction tool among...

Leveraging explainable artificial intelligence with ensemble of deep learning model for dementia prediction to enhance clinical decision support systems.

Scientific reports
The prevalence of dementia is growing worldwide due to the fast ageing of the population. Dementia is an intricate illness that is frequently produced by a mixture of genetic and environmental risk factors. There is no treatment for dementia yet; the...

Reactions and Engagement of Individuals with Dementia Toward Humanoid Assistive Robots: A Study Using the Pepper Robot.

Studies in health technology and informatics
While robot acceptance in different populations is well-studied, little is known about how individuals with dementia perceive and respond to humanoid assistive robots. This paper explores how individuals affected by dementia react to and engage with ...

Using a Robot to Address the Well-Being, Social Isolation, and Loneliness of Care Home Residents via Video Calls: Qualitative Feasibility Study.

JMIR formative research
BACKGROUND: About 40,000 people are living in Norwegian care homes, where a majority are living with a dementia diagnosis. Social isolation and loneliness are common issues affecting care home residents' quality of life. Due to visitation restriction...

Dual-stream algorithms for dementia detection: Harnessing structured and unstructured electronic health record data, a novel approach to prevalence estimation.

Alzheimer's & dementia : the journal of the Alzheimer's Association
INTRODUCTION: Identifying individuals with dementia is crucial for prevalence estimation and service planning, but reliable, scalable methods are lacking. We developed novel set algorithms using both structured and unstructured electronic health reco...