AIMC Topic: Aged

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Public hesitancy for AI-based detection of neurodegenerative diseases in France.

Scientific reports
Recent advances in artificial intelligence (AI) have made it possible to detect neurodegenerative diseases (NDDs) earlier, potentially improving patient outcomes. However, AI-based detection tools remain underutilized. We studied individual valuation...

Machine learning driven diabetes care using predictive-prescriptive analytics for personalized medication prescription.

Scientific reports
The increasing prevalence of type 2 diabetes (T2D) is a significant health concern worldwide. Effective and personalized treatment strategies are essential for improving patient outcomes and reducing healthcare costs. Machine learning (ML) has the po...

Development and validation of an improved volumetric breast density estimation model using the ResNet technique.

Biomedical physics & engineering express
. Temporal changes in volumetric breast density (VBD) may serve as prognostic biomarkers for predicting the risk of future breast cancer development. However, accurately measuring VBD from archived x-ray mammograms remains challenging. In a previous ...

Assessing the impact of information on patient attitudes toward artificial intelligence-based clinical decision support (AI/CDS): a pilot web-based SMART vignette study.

Journal of medical ethics
BACKGROUND: It is increasingly recognised that the success of artificial intelligence-based clinical decision support (AI/CDS) tools will depend on physician and patient trust, but factors impacting patients' views on clinical care reliant on AI have...

Machine learning approach effectively discriminates between Parkinson's disease and progressive supranuclear palsy: Multi-level indices of rs-fMRI.

Brain research bulletin
AIM: Parkinson's disease (PD) and progressive supranuclear palsy (PSP) present similar clinical symptoms, but their treatment options and clinical prognosis differ significantly. Therefore, we aimed to discriminate between PD and PSP based on multi-l...

Potential effects of endocrine-disrupting chemicals on preserved ratio impaired spirometry revealed by five different approaches.

Ecotoxicology and environmental safety
OBJECTIVE: Evidence from prior studies indicates that certain endocrine-disrupting chemicals (EDCs), such as phenols and phthalates, may serve as environmental risk factors for chronic obstructive pulmonary disease (COPD). However, no studies have ex...

Clinical characteristics and CKD care delivery in African American and American Indian or Alaska Native patients: A real-world cohort study.

BMC nephrology
BACKGROUND: Racially minoritized populations in the United States (US), notably African American (AA) and American Indian/Alaska Native (AI/AN), experience disproportionately higher rates of chronic kidney disease (CKD), diabetes, and hypertension co...

Early detection of ICU-acquired infections using high-frequency electronic health record data.

BMC medical informatics and decision making
BACKGROUND: Nosocomial infections are a major cause of morbidity and mortality in the ICU. Earlier identification of these complications may facilitate better clinical management and improve outcomes. We developed a dynamic prediction model that leve...

Establishment of AI-assisted diagnosis of the infraorbital posterior ethmoid cells based on deep learning.

BMC medical imaging
OBJECTIVE: To construct an artificial intelligence (AI)-assisted model for identifying the infraorbital posterior ethmoid cells (IPECs) based on deep learning using sagittal CT images.

Lysophospholipid metabolism, clinical characteristics, and artificial intelligence-based quantitative assessments of chest CT in patients with stable COPD and healthy smokers.

Scientific reports
The specific role of lysophospholipids (LysoPLs) in the pathogenesis of chronic obstructive pulmonary disease (COPD) is not yet fully understood. We determined serum LysoPLs in 20 patients with stable COPD and 20 healthy smokers using liquid chromato...