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...

Full description

Saved in:
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
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://www.mdpi.com/1424-8220/25/13/4184

Similar Items