Self-Supervised Learning-Based General Laboratory Progress Pretrained Model for Cardiovascular Event Detection

Self-Supervised Learning-Based General Laboratory Progress Pretrained Model for Cardiovascular Event Detection

Objective: Leveraging patient data through machine learning techniques in disease care offers a multitude of substantial benefits. Nonetheless, the inherent nature of patient data poses several challenges. Prevalent cases amass substantial longitudinal data owing to their patient volume and consiste...

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Bibliographic Details
Main Authors: Li-Chin Chen, Kuo-Hsuan Hung, Yi-Ju Tseng, Hsin-Yao Wang, Tse-Min Lu, Wei-Chieh Huang, Yu Tsao
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Journal of Translational Engineering in Health and Medicine
Subjects:
Cardiovascular diseases
cardiometabolic disease
disease progression
laboratory examinations
time-series data
pre-train model
Online Access:https://ieeexplore.ieee.org/document/10227304/
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