Prediction of Metastasis in Paragangliomas and Pheochromocytomas Using Machine Learning Models: Explainability Challenges

Prediction of Metastasis in Paragangliomas and Pheochromocytomas Using Machine Learning Models: Explainability Challenges

One of the main issues with paragangliomas and pheochromocytomas is that these tumors have up to a 20% rate of metastatic disease, which cannot be reliably predicted. While machine learning models hold great promise for enhancing predictive accuracy, their often opaque nature limits trust and adopti...

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Bibliographic Details
Main Authors: Carmen García-Barceló, David Gil, David Tomás, David Bernabeu
Format: Article
Language:English
Published: MDPI AG 2025-07-01
Series:Sensors
Subjects:
machine learning
explainability
data science
classification
feature selection
tumor
Online Access:https://www.mdpi.com/1424-8220/25/13/4184
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