Using Explainable Machine Learning Methods to Predict the Survivability Rate of Pediatric Respiratory Diseases

Using Explainable Machine Learning Methods to Predict the Survivability Rate of Pediatric Respiratory Diseases

The mortality rate due to chronic pediatric respiratory diseases is increasing every year and it is important to assess the severity of these diseases. As symptoms of several pediatric respiratory disorders are frequently identical, identification might be difficult due to the ongoing spread of resp...

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Bibliographic Details
Main Authors: Roshan Kumar, V Srirama, Krishnaraj Chadaga, H Muralikrishna, Niranjana Sampathila, Srikanth Prabhu, Rajagopala Chadaga
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Clinical variables
explainable artificial intelligence
machine learning
pediatric respiratory diseases
Online Access:https://ieeexplore.ieee.org/document/10794659/
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