AIMC Topic: Aged

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A heart failure classification model from radial artery pulse wave using LSTM neural networks.

BMC medical informatics and decision making
BACKGROUND: Heart failure (HF) represents a pressing global health issue demanding innovative and accessible approaches for early detection. Non-invasive, rapid, and cost-effective techniques utilizing deep learning (DL) hold significant promise for ...

Deep learning-based automatic facial symmetry scoring in peripheral facial palsy.

Scientific reports
Unilateral peripheral facial palsy (PFP) results in facial asymmetry and functional impairment, reducing quality of life. Accurate, objective assessment is vital for monitoring and rehabilitation. This study presents an automated method utilizes stan...

Deep learning for classifying imaging patterns of interstitial lung disease associated with idiopathic inflammatory myopathies.

Scientific reports
Diagnosing and classifying the imaging patterns of idiopathic inflammatory myopathies-associated interstitial lung disease (IIM-ILD) is a crucial but challenging task requiring specialized physicians' expertise. This study aims to develop and validat...

Explainable machine learning identifies key quality-of-life-related predictors of arthritis status: evidence from the China health and retirement longitudinal study.

Health and quality of life outcomes
BACKGROUND: Arthritis is a prevalent chronic disease substantially impacting patients' quality of life (QoL). While identifying key determinants associated with arthritis is critical for targeted interventions, traditional statistical methods often s...

Exploring the potential relationship between kidney disease index and cognitive dysfunction: a machine learning approach with NHANES data.

BMC geriatrics
OBJECTIVE: This study investigates the relationship between the Kidney Disease Index (KDI) and cognitive function, evaluating its potential as a predictive marker for cognitive impairment in older adults. We also compare the performance of KDI with t...

Comparison of the number of peripapillary perforating scleral vessels between glaucomatous eyes and healthy eyes.

Scientific reports
This study aimed to compare the number of peripapillary perforating scleral vessels (PPSVs) between eyes with and without glaucoma. A retrospective case-control analysis was performed on patients with glaucoma and control participants who underwent s...

Advanced smart human activity recognition system for disabled people using artificial intelligence with snake optimizer techniques.

Scientific reports
Human Activity Recognition (HAR) has become an active research area in recent years due to its applicability in various domains and the growing need for convenient facilities and intelligent homes for the elderly. Physical activity tends to decrease ...

Development of a deep learning method to identify acute ischaemic stroke lesions on brain CT.

Stroke and vascular neurology
BACKGROUND: CT is commonly used to image patients with ischaemic stroke but radiologist interpretation may be delayed. Machine learning techniques can provide rapid automated CT assessment but are usually developed from annotated images which necessa...

Enhancing the early detection of Alzheimer's disease using an integrated CNN-LSTM framework: A robust approach for fMRI-based multi-stage classification.

PloS one
Alzheimer's Disease poses a significant challenge as a progressive and irreversible neurological condition striking the elderly population. Its incurable nature correlates with a significant rise in death rates. However, early detection can slow its ...

Causal effect of conventional anti-dementia drugs on economic burden: an orthogonal double/debiased machine learning approach.

BMC geriatrics
BACKGROUND: The Inflation Reduction Act (IRA) did not introduce a cap on out-of-pocket (OOP) for newly approved Alzheimer's Disease (AD) drugs, such as lecanemab which is covered under Medicare Part B. Therefore, expanding the use of conventional ant...