COVID-19 Severity Classification Using Hybrid Feature Extraction: Integrating Persistent Homology, Convolutional Neural Networks and Vision Transformers

COVID-19 Severity Classification Using Hybrid Feature Extraction: Integrating Persistent Homology, Convolutional Neural Networks and Vision Transformers

This paper introduces a model that automates the diagnosis of a patient’s condition, reducing reliance on highly trained professionals, particularly in resource-constrained settings. To ensure data consistency, the dataset was preprocessed for uniformity in size, format, and color channels. Image qu...

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Bibliographic Details
Main Authors: Redet Assefa, Adane Mamuye, Marco Piangerelli
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Big Data and Cognitive Computing
Subjects:
COVID-19
chest X-ray
vision transformer
self-attention
CoatNet
topological data analysis
Online Access:https://www.mdpi.com/2504-2289/9/4/83
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