A comprehensive review and experimental comparison of deep learning methods for automated hemorrhage detection-Reference-Cited by-同舟云学术

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A comprehensive review and experimental comparison of deep learning methods for automated hemorrhage detection

Published:2024-07 Issue: Volume:133 Page:108192
ISSN:0952-1976
Container-title:Engineering Applications of Artificial Intelligence
language:en
Short-container-title:Engineering Applications of Artificial Intelligence

Author:

Neethi A.S.^ORCID,Kannath Santhosh Kumar,Kumar Adarsh Anil,Mathew Jimson,Rajan Jeny

Funder

Ministry of Science and Technology, Pakistan

India Ministry of Science & Technology Department of Biotechnology

Publisher

Elsevier BV

Reference186 articles.

1. Federated learning and differential privacy for medical image analysis;Adnan;Sci. Rep.,2022

2. Automated intracranial hemorrhage detection in traumatic brain injury using 3D CNN;Agrawal;J. Neurosci. Rural Pract.,2023

3. A systematic review of trustworthy and explainable artificial intelligence in healthcare: Assessment of quality, bias risk, and data fusion;Albahri;Inf. Fusion,2023

4. Fusion-based deep learning with nature-inspired algorithm for intracerebral haemorrhage diagnosis;Alfaer;J. Healthc. Eng.,2022

5. A joint convolutional-recurrent neural network with an attention mechanism for detecting intracranial hemorrhage on noncontrast head CT;Alis;Sci. Rep.,2022

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