Early Risk Prediction in Acute Aortic Syndrome on Clinical Data Using Machine Learning

Early Risk Prediction in Acute Aortic Syndrome on Clinical Data Using Machine Learning

This study explores machine learning’s potential for early Acute Aortic Syndrome (AAS) prediction by integrating and cleaning extensive clinical datasets from 68 emergency departments in the USA, covering the medical histories of nearly 150,000 patients from 2021 to 2022. Utilizing various data-spli...

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Bibliographic Details
Main Authors: Mehdi Tavafi, Kalpdrum Passi, Robert Ohle
Format: Article
Language:English
Published: MDPI AG 2025-04-01
Series:Algorithms
Subjects:
machine learning
acute aortic syndrome (AAS)
clinical data
SMOTE method
feature extraction
Principal Component Analysis (PCA)
Online Access:https://www.mdpi.com/1999-4893/18/5/257
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