AIMC Topic: Middle Aged

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Prioritization of patients at risk of heart attack using a novel full-objective ITARA based on Random Forest and Decision tree.

Scientific reports
Heart attacks remain a major cause of morbidity and mortality, particularly among middle-aged and older adults, often aggravated by unhealthy lifestyles and limited preventive care. Early identification and prioritization of at-risk individuals are e...

A noninvasive machine learning model using a complete blood count for screening of primary vitreoretinal lymphoma.

Nature communications
Primary vitreoretinal lymphoma (PVRL) is a rare and aggressive intraocular malignancy that is frequently misdiagnosed because of its nonspecific early manifestations and the lack of effective screening tools. We conduct a multicentre case-control stu...

Patient Attitudes Toward Ambient Voice Technology: Preimplementation Patient Survey in an Academic Medical Center.

JMIR medical informatics
BACKGROUND: Many institutions are in various stages of deploying an artificial intelligence (AI) scribe system for clinic electronic health record (EHR) documentation. In anticipation of the University of California, Davis Health's deployment of an A...

AI-Powered Thermography for Diabetic Foot Risk Stratification: Multicenter Cross-Sectional Study.

JMIR formative research
BACKGROUND: Diabetic foot complications are among the most severe and costly outcomes associated with diabetes, with high prevalence particularly in the Middle East and North Africa region. Current screening tools are often limited by subjectivity, i...

Risk Prediction of Major Adverse Cardiovascular Events Within One Year After Percutaneous Coronary Intervention in Patients With Acute Coronary Syndrome: Machine Learning-Based Time-to-Event Analysis.

JMIR medical informatics
BACKGROUND: Patients with acute coronary syndrome (ACS) who undergo percutaneous coronary intervention (PCI) remain at high risk for major adverse cardiovascular events (MACE). Conventional risk scores may not capture dynamic or nonlinear changes in ...

Machine Learning Models To Characterize the Association of the Gut Microbiota with Osteopenia and Osteoporosis: A Multi-Cohort Study.

Current microbiology
Emerging evidence suggests that gut microbiota dysbiosis is associated with bone metabolism disorders, including osteopenia (ON) and osteoporosis (OP). However, multi-cohort integrated and association analyses remain underexplored. We conducted a com...

Integrated Metabolomics and Lipidomics of Tissue and Serum Reveal Mechanistic Pathways and Lipid Signatures Distinguishing Meningioma Grades.

Journal of proteome research
Meningioma, the most prevalent primary intracranial tumor, presents significant clinical challenges due to unclear molecular mechanisms underlying its progression from low-grade (LG) to high-grade (HG) and lack of grade-specific biomarkers. Here, we ...

Association of the dietary index for gut microbiota with metabolic syndrome and its components combining interpretable machine learning algorithms.

Journal of health, population, and nutrition
BACKGROUND: Previous studies have emphasized the critical role of diet and gut microbiome in Metabolic syndrome (MetS). The dietary index for gut microbiota (DI-GM) represents a novel dietary index that effectively reflects the diversity of gut micro...

Interpretable and reproducible machine learning model for coronary calcification and segment-level stenoses stratification on computed tomography angiography.

BMC medicine
BACKGROUND: Coronary computed tomography angiography (CCTA) is widely used as a first-line tool for diagnosing and managing coronary artery disease (CAD), and machine learning (ML)-based analysis shows promise for quantitative CAD assessment.

Artificial intelligence-based diagnosis of diabetic kidney disease using urinary VOC biosensor data.

BMC nephrology
BACKGROUND: Diabetic kidney disease (DKD) remains a leading cause of chronic kidney disease worldwide. However, current diagnostic methods rely on indirect biomarkers or invasive renal biopsy. This study aimed to evaluate the feasibility of urinary v...