Integrating deep learning in public health: a novel approach to PICC-RVT risk assessment

Integrating deep learning in public health: a novel approach to PICC-RVT risk assessment

BackgroundMachine learning is pivotal for predicting Peripherally Inserted Central Catheter-related venous thrombosis (PICC-RVT) risk, facilitating early diagnosis and proactive treatment. Existing models often assess PICC-RVT risk as static and discrete outcomes, which may limit their practical app...

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Bibliographic Details
Main Authors: Yue Li, Shengxiao Nie, Lei Wang, Dongsheng Li, Shengmiao Ma, Ting Li, Hong Sun
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-01-01
Series:Frontiers in Public Health
Subjects:
artificial intelligence
machine learning
peripherally inserted central catheter
time-to-event
thrombosis
Online Access:https://www.frontiersin.org/articles/10.3389/fpubh.2024.1445425/full
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