AIMC Topic: Aged

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Prediction of Moderate-to-Severe Sepsis-Associated Acute Kidney Injury Using a Dual-Timepoint Machine Learning Model: Development, Multiregional Validation, and Clinical Deployment Study.

Journal of medical Internet research
BACKGROUND: Sepsis-associated acute kidney injury (SA-AKI) is a frequent and life-threatening complication in patients in the intensive care unit (ICU), significantly increasing both mortality rates and the risk of chronic kidney dysfunction. However...

Assessing the feasibility of deep learning-based attenuation correction using photon emission data inF-FDG images for dedicated head and neck PET scanners.

Biomedical physics & engineering express
This study aimed to evaluate the use of deep learning techniques to produce measured attenuation-corrected (MAC) images from non-attenuation-corrected (NAC) F-FDG PET images, focusing on head and neck imaging. A Residual Network (ResNet) was used to ...

An interpretable generative multimodal neuroimaging-genomics framework for decoding Alzheimer's disease.

Journal of neural engineering
Alzheimer's disease (AD) is the most prevalent form of dementia worldwide, encompassing a prodromal stage known as mild cognitive impairment (MCI), where patients may either progress to AD or remain stable. The objective of the work was to capture st...

Spatial distribution patterns and risk factors of hookworm disease in China: A study based on successive national surveillance.

PLoS neglected tropical diseases
BACKGROUND: Hookworm infection, a neglected tropical disease (NTD) causing iron-deficiency anaemia and malnutrition in low-income populations with poor sanitation, poses a considerable public health challenge in China and worldwide.

Effects of robot assisted mirror therapy on motor function and cortical activation in patients with right hemisphere damage.

Scientific reports
Robot-assisted mirror therapy (MRT) is a cutting-edge rehabilitative treatment that combines mirror therapy and rehabilitation robots and can improve stroke patient participation in rehabilitation training. The aim of this study was to investigate th...

Automated deep U-Net model for ischemic stroke lesion segmentation in the sub-acute phase.

Scientific reports
Manual segmentation of sub-acute ischemic stroke lesions in fluid-attenuated inversion recovery magnetic resonance imaging (FLAIR MRI) is time-consuming and subject to inter-observer variability, limiting clinical workflow efficiency. To develop and ...

Transformer-based AI approach to unravel long-term, time-dependent prognostic complexity in patients with advanced NSCLC and PD-L1 ≥50%: insights from the pembrolizumab 5-year global registry.

Journal for immunotherapy of cancer
BACKGROUND: With nearly one-third of patients with advanced non-small cell lung cancer (NSCLC) and PD-L1 Tumor Proportion Score≥50% surviving beyond 5 years following first-line pembrolizumab, long-term outcomes challenge traditional paradigms of can...

Alzheimer's disease classification using a hybrid deep learning approach with multi-layer U-net segmentation and XAI driven analysis.

PloS one
Alzheimer's disease (AD) is a neurodegenerative illness causing a significant decrease in cognitive function, and early, accurate diagnosis is of great therapeutic and diagnostic value. Currently, there is promising potential for applying various typ...

The Impact of Comorbidity Patterns on Clinical Outcomes in Heart Failure: A Machine Learning-Based Cluster Analysis.

The American journal of cardiology
Heart failure (HF) is a major global health burden, and complex comorbidity patterns can worsen clinical outcomes and complicate patient care. This study aimed to identify distinct comorbidity-based clusters among HF patients and evaluate their assoc...