AIMC Topic: Middle Aged

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Chronic Pain Prevalence, Opioid Use, and Primary Care Provider Opioid Prescription Patterns in the U.S. from 2017 to 2019 Derived from Medicaid Claims Data.

Studies in health technology and informatics
Chronic non-cancer pain (CNCP) is a major health concern in the United States, incurring substantial healthcare costs and frequently requiring opioid therapy in primary care. This retrospective cross-sectional study used Medicaid claims data from six...

Early Identification of Vitamin D Deficiency Risk Through Public Health Screening Data.

Studies in health technology and informatics
Metabolic syndrome, characterized by central obesity, hypertension, hyperglycemia, dyslipidemia, and reduced high-density lipoprotein levels, significantly increases the risk of cardiovascular diseases. Vitamin D, essential for calcium regulation and...

Personalized Prediction of Chronic Kidney Disease Progression in Patients with Chronic Kidney Disease Stages 3-5: A Multicenter Study Using the Machine Learning Approach.

Studies in health technology and informatics
Chronic Kidney Disease (CKD) is a prevalent and progressive condition that can lead to end-stage renal disease (ESRD) if left unmanaged. Accurate prediction of CKD progression, particularly in patients with CKD stages 3-5, is essential for early inte...

Early Detection of Acute Coronary Syndrome Using a Mobile Digital Health Application.

Studies in health technology and informatics
Early detection of acute coronary syndrome (ACS) is vital for reducing ischemic time and preserving more heart muscle.Chest pain is the most common symptom of acute coronary syndrome (ACS). This study used a quick chest pain assessment questionnaire ...

Development and Validation of Machine-Learning Algorithms to Predict the Onset of Depression Using Electronic Health Record Data: A Prognostic Modeling Study.

Studies in health technology and informatics
INTRODUCTION: Early detection and intervention are crucial for reducing the impacts of depression and associated healthcare costs. Few studies have used electronic health records (EHR) and machine learning (ML) with a longitudinal design to predict d...

Development of Multivariable Prediction Models for 30-Day Risk of Readmission After COPD Hospital Admission: A Retrospective Cohort Study Using Electronic Medical Record Data from 7 Hospitals.

Studies in health technology and informatics
BACKGROUND: Approximately 20% of patients who are discharged from hospital for an acute exacerbation of COPD (AECOPD) are readmitted within 30 days. Prediction scores are helpful to identify those who are at higher risk of readmission, such that they...

Lower Extremity Bypass Surveillance and Peak Systolic Velocities Value Prediction Using Recurrent Neural Networks.

Studies in health technology and informatics
Routine duplex ultrasound surveillance is recommended after femoral-popliteal and femoral-tibial-pedal vein bypass grafts at various post-operative intervals. Currently, there is no systematic method for bypass graft surveillance using a set of peak ...

Predicting Nephrectomy Risk in Patients with Renal Cancer Using Real-World Electronic Health Records.

Studies in health technology and informatics
Nephrectomy, the surgical removal of a kidney, is a critical treatment for renal cancer, and predicting its likelihood can help guide clinical decision-making and optimize preoperative planning. This study utilized real-world electronic health record...

Detection of Brain Cancer Using Genome-wide Cell-free DNA Fragmentomes.

Cancer discovery
UNLABELLED: Diagnostic delays in patients with brain cancer are common and can impact patient outcome. Development of a blood-based assay for detection of brain cancers could accelerate brain cancer diagnosis. In this study, we analyzed genome-wide c...

Predicting p53 Status in IDH-Mutant Gliomas Using MRI-Based Radiomic Model.

Cancer medicine
OBJECTIVES: Accurate and noninvasive detection of p53 status in isocitrate dehydrogenase mutant (IDH-mt) glioma is clinically meaningful for molecular stratification of glioma, yet it remains challenging. We aimed to investigate the diagnostic effica...