Between Two Worlds: Investigating the Intersection of Human Expertise and Machine Learning in the Case of Coronary Artery Disease Diagnosis

Between Two Worlds: Investigating the Intersection of Human Expertise and Machine Learning in the Case of Coronary Artery Disease Diagnosis

Coronary artery disease (CAD) presents a significant global health burden, with early and accurate diagnostics crucial for effective management and treatment strategies. This study evaluates the efficacy of human evaluators compared to a Random Forest (RF) machine learning model in predicting CAD ri...

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Bibliographic Details
Main Authors: Ioannis D. Apostolopoulos, Nikolaos I. Papandrianos, Dimitrios J. Apostolopoulos, Elpiniki Papageorgiou
Format: Article
Language:English
Published: MDPI AG 2024-09-01
Series:Bioengineering
Subjects:
coronary artery disease
machine learning
random forest
probability calibration
Online Access:https://www.mdpi.com/2306-5354/11/10/957
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