This multivariate analysis also suggested the presence of previously unrecognized subclusters within the favorable prognosis category, indicating the potential for finer risk stratification.
The latent profile analysis was used to identify the self-efficacy groups of young and middle-aged patients with aortic ...
There are more candidates on the waitlist for a liver transplant than there are available organs, yet about half the time a ...
We show that, compared with surgeon predictions and existing risk-prediction tools, our machine-learning model can enhance ...
Donation after circulatory death (DCD) procurements provide an opportunity to alleviate the limited organ supply for solid ...
Wearables, Mobile Health (m-Health), Real-Time Monitoring Share and Cite: Alqarni, A. (2025) Analysis of Decision Support ...
Abstract: The work's objective is to assess how well the classification techniques of logistic regression and support vector machine predict handwritten digits. A Digit dataset with 985 records is ...
FIU Researchers are training AI to detect heart conditions, like aortic stenosis and heart failure, by analyzing heart sound data to improve early diagnosis and risk prediction. The future of heart ...
A new Apple-supported study argues that your behavior data (movement, sleep, exercise, etc.) can often be a stronger health signal than traditional biometric measurements like heart rate or blood ...
Researchers at Katanemo Labs have introduced Arch-Router, a new routing model and framework designed to intelligently map user queries to the most suitable large language model (LLM). For enterprises ...
Introduction: Arrhythmia, characterized by irregular heartbeats, can range from harmless to potentially life-threatening disturbances in heart rhythm. Effective detection and classification of ...
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