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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محفوظ في:

التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Aftab Hussain (1385985) (author)
مؤلفون آخرون:	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)
منشور في:	2022
الموضوعات:	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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An Attention-Based ResNet Architecture for Acute Hemorrhage Detection and Classification: Toward a Health 4.0 Digital Twin Study

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