AIMC Topic: Aged
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Predicting 28-day all-cause mortality in patients admitted to intensive care units with pre-existing chronic heart failure using the stress hyperglycemia ratio: a machine learning-driven retrospective cohort analysis.
Cardiovascular diabetology
Jan 8, 2025
Chronic heart failure (CHF) poses a significant threat to human health. The stress hyperglycemia ratio (SHR) is a novel metric for accurately assessing stress hyperglycemia, which has been correlated with adverse outcomes in various major diseases. H...
Female
Patient Admission
Risk Factors
Aged
Aged, 80 and over
Male
Biomarkers
Prognosis
Retrospective Studies
Intensive Care Units
Middle Aged
Risk Assessment
Blood Glucose
Hyperglycemia
Time Factors
Chronic Disease
Predictive Value of Tests
Humans
Cause of Death
Machine Learning
Heart Failure
Decision Support Techniques
Databases, Factual
Blood metal levels predict digestive tract cancer risk using machine learning in a U.S. cohort.
Scientific reports
Jan 8, 2025
BACKGROUND: Environmental metal exposure has been implicated in the development of digestive tract cancers, although the specific associations remain poorly defined. This study aimed to investigate the relationship between blood metal levels and the ...
Artificial intelligence empowered voice generation for amyotrophic lateral sclerosis patients.
Scientific reports
Jan 8, 2025
Amyotrophic Lateral Sclerosis (ALS) is a neurodegenerative disease that can result in a progressive loss of speech due to bulbar dysfunction, which can have significant negative impact on the patient's mental well-being. Alternative Augmentative Comm...
Artificial intelligence for body composition assessment focusing on sarcopenia.
Scientific reports
Jan 8, 2025
This study aimed to address the limitations of conventional methods for measuring skeletal muscle mass for sarcopenia diagnosis by introducing an artificial intelligence (AI) system for direct computed tomography (CT) analysis. The primary focus was ...
Deep Learning-Based Super-Resolution Reconstruction on Undersampled Brain Diffusion-Weighted MRI for Infarction Stroke: A Comparison to Conventional Iterative Reconstruction.
AJNR. American journal of neuroradiology
Jan 8, 2025
BACKGROUND AND PURPOSE: DWI is crucial for detecting infarction stroke. However, its spatial resolution is often limited, hindering accurate lesion visualization. Our aim was to evaluate the image quality and diagnostic confidence of deep learning (D...
Designing a Multimodal and Culturally Relevant Alzheimer Disease and Related Dementia Generative Artificial Intelligence Tool for Black American Informal Caregivers: Cognitive Walk-Through Usability Study.
JMIR aging
Jan 8, 2025
BACKGROUND: Many members of Black American communities, faced with the high prevalence of Alzheimer disease and related dementias (ADRD) within their demographic, find themselves taking on the role of informal caregivers. Despite being the primary in...
Predicting cardiovascular disease in patients with mental illness using machine learning.
European psychiatry : the journal of the Association of European Psychiatrists
Jan 8, 2025
BACKGROUND: Cardiovascular disease (CVD) is twice as prevalent among individuals with mental illness compared to the general population. Prevention strategies exist but require accurate risk prediction. This study aimed to develop and validate a mach...
Automated Idiopathic Normal Pressure Hydrocephalus Diagnosis via Artificial Intelligence-Based 3D T1 MRI Volumetric Analysis.
AJNR. American journal of neuroradiology
Jan 8, 2025
BACKGROUND AND PURPOSE: Idiopathic normal pressure hydrocephalus (iNPH) is reversible dementia that is underdiagnosed. The purpose of this study was to develop an automated diagnostic method for iNPH using artificial intelligence techniques with a T1...
DANTE-CAIPI Accelerated Contrast-Enhanced 3D T1: Deep Learning-Based Image Quality Improvement for Vessel Wall MRI.
AJNR. American journal of neuroradiology
Jan 8, 2025
BACKGROUND AND PURPOSE: Accelerated and blood-suppressed postcontrast 3D intracranial vessel wall MRI (IVW) enables high-resolution rapid scanning but is associated with low SNR. We hypothesized that a deep-learning (DL) denoising algorithm applied t...
Multimodal data deep learning method for predicting symptomatic pneumonitis caused by lung cancer radiotherapy combined with immunotherapy.
Frontiers in immunology
Jan 8, 2025
OBJECTIVES: The pairing of immunotherapy and radiotherapy in the treatment of locally advanced nonsmall cell lung cancer (NSCLC) has shown promise. By combining radiotherapy with immunotherapy, the synergistic effects of these modalities not only bol...
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