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Using C4.5 Algorithm to Gain Insights on Stakeholder Engagement and Use of Artificial Intelligence on Social Media in Dementia Caregiving Disparity Research.
Studies in health technology and informatics
Apr 8, 2025
We applied machine learning techniques to build models that predict perceived risks and benefits of using artificial intelligence (AI) algorithms to recruit African American informal caregivers for clinical trials and general health disparity researc...
Predicting Prostate Cancer Diagnosis Using Machine Learning Analysis of Healthcare Utilization Patterns.
Studies in health technology and informatics
Apr 8, 2025
This study investigated healthcare utilization patterns prior to prostate cancer diagnoses, aiming to develop machine learning models for early prediction of cancer diagnosis. Data from the All of Us Research Program was used, focusing on adult patie...
Exploring the Impact of PA and Sedentary Behavior on Gout Risk in Hyperuricemia: Insights From Machine Learning and SHAP Analysis.
International journal of rheumatic diseases
Apr 1, 2025
BACKGROUND: Individuals with hyperuricemia (HUA) are widely recognized as being at increased risk for gout. This study aimed to investigate how physical activity (PA) duration and sedentary duration impact gout risk in individuals with HUA and to dev...
AI in health care: closing the revenue cycle gap.
The American journal of managed care
Apr 1, 2025
This commentary explores the current state, challenges, and potential of artificial intelligence (AI) in health care revenue cycle management, emphasizing collaboration, data standardization, and targeted implementation to enhance adoption.
Suspicious of AI? Perceived autonomy and interdependence predict AI-related conspiracy beliefs.
The British journal of social psychology
Apr 1, 2025
As artificial intelligence (AI) evolves, conspiracy theories have emerged that authorities will use AI to oppress humanity, or AI itself will. We propose that perceived high autonomy and low interdependence of AI increase AI-related conspiracy belief...
Determining health care cost drivers in older Hodgkin lymphoma survivors using interpretable machine learning methods.
Journal of managed care & specialty pharmacy
Apr 1, 2025
BACKGROUND: The cost of health care for patients with Hodgkin lymphoma (HL) is projected to rise, making it essential to understand expenditure drivers across different demographics, including the older adult population. Although older HL patients co...
Electrocardiogram-based deep learning to predict left ventricular systolic dysfunction in paediatric and adult congenital heart disease in the USA: a multicentre modelling study.
The Lancet. Digital health
Apr 1, 2025
BACKGROUND: Left ventricular systolic dysfunction (LVSD) is independently associated with cardiovascular events in patients with congenital heart disease. Although artificial intelligence-enhanced electrocardiogram (AI-ECG) analysis is predictive of ...
General Applicability of Existing College of American Pathologists Accreditation Requirements to Clinical Implementation of Machine Learning-Based Methods in Molecular Oncology Testing.
Archives of pathology & laboratory medicine
Apr 1, 2025
CONTEXT.—: The College of American Pathologists (CAP) accreditation requirements for clinical laboratory testing help ensure laboratories implement and maintain systems and processes that are associated with quality. Machine learning (ML)-based model...
Key Predictors of Generativity in Adulthood: A Machine Learning Analysis.
The journals of gerontology. Series B, Psychological sciences and social sciences
Mar 12, 2025
OBJECTIVES: This study aimed to explore a broad range of predictors of generativity in older adults. The study included over 60 predictors across multiple domains, including personality, daily functioning, socioeconomic factors, health status, and me...
Artificial intelligence-derived electrocardiographic aging and risk of atrial fibrillation: a multi-national study.
European heart journal
Mar 3, 2025
BACKGROUND AND AIMS: Artificial intelligence (AI) algorithms in 12-lead electrocardiogram (ECG) provides promising age prediction methods. This study investigated whether the discrepancy between ECG-derived AI-predicted age (AI-ECG age) and chronolog...
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