An Attention-Based ResNet Architecture for Acute Hemorrhage Detection and Classification: Toward a Health 4.0 Digital Twin Study

An Attention-Based ResNet Architecture for Acute Hemorrhage Detection and Classification: Toward a Health 4.0 Digital Twin Study

<p dir="ltr">Due to the advancement of digital twin (DT) technology, Health 4.0 applications have become reality and starting to take roots. In this article, we focus on intracranial hemorrhage (ICH) which is a life-threatening emergency that needs immediate diagnosis and treatment....

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Bibliographic Details
Main Author: Aftab Hussain (1385985) (author)
Other Authors: Muhammad Usman Yaseen (9074552) (author), Muhammad Imran (282621) (author), Muhammad Waqar (500788) (author), Adnan Akhunzada (3134064) (author), Mohammad Al-Ja'afreh (17542137) (author), Abdulmotaleb El Saddik (17542140) (author)
Published: 2022
Subjects:
Engineering
Biomedical engineering
Health sciences
Health services and systems
Information and computing sciences
Artificial intelligence
Data management and data science
Machine learning
Computed tomography
Hemorrhaging
Feature extraction
Brain modeling
Deep learning
Principal component analysis
Data augmentation
Deep convolutional generative adversarial network
Digital twin
Health 4.0
Intracranial hemorrhage
ResNet-152V2
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