AIMC Topic: Aged

Clear Filters Showing 3211 to 3220 of 14227 articles

Predicting cardiovascular disease in patients with mental illness using machine learning.

European psychiatry : the journal of the Association of European Psychiatrists
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
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
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
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...

Interpretable machine learning-based prediction of 28-day mortality in ICU patients with sepsis: a multicenter retrospective study.

Frontiers in cellular and infection microbiology
BACKGROUND: Sepsis is a major cause of mortality in intensive care units (ICUs) and continues to pose a significant global health challenge, with sepsis-related deaths contributing substantially to the overall burden on healthcare systems worldwide. ...

Comparable Performance Between Automatic and Manual Laryngeal and Hypopharyngeal Gross Tumor Volume Delineations Validated With Pathology.

International journal of radiation oncology, biology, physics
PURPOSE: Deep learning is a promising approach to increase reproducibility and time-efficiency of gross tumor volume (GTV) delineation in head and neck cancer, but model evaluation primarily relies on manual GTV delineations as reference annotation, ...

Multilabel segmentation and analysis of skeletal muscle and adipose tissue in routine abdominal CT scans.

Computers in biology and medicine
PURPOSE: This paper presents a deep learning-based multi-label segmentation network that extracts a total of three separate adipose tissues and five different muscle tissues in CT slices of the third lumbar vertebra and additionally improves the segm...

Prediction of mortality in intensive care unit with short-term heart rate variability: Machine learning-based analysis of the MIMIC-III database.

Computers in biology and medicine
BACKGROUND: Prognosis prediction in the intensive care unit (ICU) traditionally relied on physiological scoring systems based on clinical indicators at admission. Electrocardiogram (ECG) provides easily accessible information, with heart rate variabi...

Nationwide real-world implementation of AI for cancer detection in population-based mammography screening.

Nature medicine
Artificial intelligence (AI) in mammography screening has shown promise in retrospective evaluations, but few prospective studies exist. PRAIM is an observational, multicenter, real-world, noninferiority, implementation study comparing the performanc...

Prediction of late-onset depression in the elderly Korean population using machine learning algorithms.

Scientific reports
Late-onset depression (LOD) refers to depression that newly appears in elderly individuals without prior depression episodes. Predicting future depression is crucial for mitigating the risk of major depression in prospective patients. This study aims...