AIMC Topic: Aged, 80 and over

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Predicting response to anti-VEGF therapy in neovascular age-related macular degeneration using random forest and SHAP algorithms.

Photodiagnosis and photodynamic therapy
PURPOSE: This study aimed to establish and validate a prediction model based on machine learning methods and SHAP algorithm to predict response to anti-vascular endothelial growth factor (VEGF) therapy in neovascular age-related macular degeneration ...

Deep-Diffeomorphic Networks for Conditional Brain Templates.

Human brain mapping
Deformable brain templates are an important tool in many neuroimaging analyses. Conditional templates (e.g., age-specific templates) have advantages over single population templates by enabling improved registration accuracy and capturing common proc...

Individual thigh muscle and proximal femoral features predict displacement in femoral neck Fractures: An AI-driven CT analysis.

Computers in biology and medicine
INTRODUCTION: Hip fractures, particularly among the elderly, impose a significant public health burden due to increased morbidity and mortality. Femoral neck fractures, commonly resulting from low-energy falls, can lead to severe complications such a...

Exploring the diagnostic potential of EEG theta power and interhemispheric correlation of temporal lobe activities in Alzheimer's Disease through random forest analysis.

Computers in biology and medicine
BACKGROUND: Considering the prevalence of Alzheimer's Disease (AD) among the aging population and the limited means of treatment, early detection emerges as a crucial focus area whereas electroencephalography (EEG) provides a promising diagnostic too...

Sharing patient technology preferences with care networks: Stakeholders' views of the "Let's Talk Tech" decision aid for dementia care.

Journal of Alzheimer's disease : JAD
BackgroundLet's Talk Tech (LTT) is a self-administered web intervention for people with memory loss and their care partners that supports decision-making about digital health technologies. In past work, dyads wanted to share LTT preference reports wi...

AI-based prediction of left bundle branch block risk post-TAVI using pre-implantation clinical parameters.

Future cardiology
BACKGROUND AND AIMS: Transcatheter Aortic Valve Implantation (TAVI) has revolutionized the treatment of severe aortic stenosis. Although its clinical efficacy is well established, the development of new-onset left bundle branch block (LBBB) following...

Development of a deep neural network model for ultra-early neurological deterioration in ischemic stroke and analysis of associated risk factors.

Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
BACKGROUND: In this study, we established a deep neural network (DNN)-based predictive model, aiming to provide a basis for improving the treatment prognosis of early neurological deterioration (END) in patients with ultra-early ischemic stroke after...

Estimating individualized effectiveness of receiving successful recanalization for ischemic stroke cases using machine learning techniques.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
OBJECTIVES: Directly measuring the causal effect of mechanical thrombectomy (MT) for each ischemic stroke patient remains challenging, as it is impossible to observe the outcomes for both with and without successful recanalization in the same individ...