AIMC Topic: Aged

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Dynamic Changes in Metabolic Syndrome Scores and New-Onset Stroke Risk in Middle-Aged and Older Adults: A Nationwide Prospective Cohort Study in China Aligned With Predictive, Preventive, and Personalized Medicine.

Journal of the American Heart Association
BACKGROUND: Despite the established link between metabolic syndrome (MetS) and stroke incidence, the effects of dynamic and cumulative MetS scores on stroke risk among middle-aged and older populations in China remain inadequately explored. Furthermo...

Deep Learning-Based Continuous QT Monitoring to Identify High-Risk Prolongation Events After Class III Antiarrhythmic Initiation.

Circulation
BACKGROUND: Drug-induced QT prolongation after successful inpatient loading of class III antiarrhythmics may occur during routine outpatient care. Insertable cardiac monitors offer continuous signals but are limited by single-lead configuration. We h...

Prognostic Value of a Coronary Computed Tomography Angiography-Derived Ischemia Algorithm: Comparison Against Hybrid Coronary Computed Tomography Angiography/Positron Emission Tomography Imaging.

Journal of the American Heart Association
BACKGROUND: Artificial intelligence-guided quantitative computed tomography ischemia (AI-QCT) is a novel machine-learning method for predicting myocardial ischemia from coronary computed tomography angiography (CCTA). This observational cohort study ...

Parkinson's disease severity clustering based on gait activity from mobile device.

Scientific reports
Parkinson's disease (PD) is a neurodegenerative disorder characterized by motor symptoms, including gait impairments, which significantly affect patient mobility and quality of life. An accurate assessment of the severity of PD is crucial for clinica...

A large language model for delirium prediction in the intensive care unit using structured electronic health records.

Scientific reports
Delirium is an acute syndrome characterized by fluctuating attention, cognitive impairment, and severe disorganization of behavior, which has been shown to affect up to 31% of patients in the intensive care unit (ICU). Early detection can enable time...

Integrating machine learning and time-to-event models to explain and predict risk of hospitalization due to dengue in Colombia.

Scientific reports
Arboviral diseases such as dengue pose major public health challenges in endemic regions, notably in Norte de Santander (Colombia), where they place substantial pressure on healthcare services. We analyzed 8,814 confirmed dengue cases reported to the...

Preoperative plasma ceramide profiling coupled with machine learning accurately predicts recurrence of hepatocellular carcinoma after resection.

Lipids in health and disease
BACKGROUND: Accurate stratification of recurrence risk after curative resection remains a critical challenge in the management of hepatocellular carcinoma (HCC). Dysregulated ceramide (CER) metabolism has been implicated in HCC progression and relaps...

Torso synthetic CT generation by integrating deep learning and segmentation for FDG-PET/MR attenuation correction.

Biomedical physics & engineering express
Positron Emission Tomography/Magnetic Resonance () offers benefits over PET/CT including simultaneous PET and MR acquisition, intrinsic spatial registration accuracy, MR-based functional information, and superior soft tissue contrast. However, accura...

Interpretable machine learning for cardiovascular risk prediction: Insights from NHANES dietary and health data.

PloS one
BACKGROUND: Cardiovascular diseases (CVD) are one of the leading global causes of death, which requires an accurate early prediction. This study aimed to develop transparent machine learning (ML) models using National Health and Nutrition Examination...