ISC-DL: DL For Diagnosis of Ischemic Stroke

Document Type : Original Article

Authors

1 MSA University ESE Department 6th Of October Giza Government Egypt

2 MSA University, ESE Department, 6th of October, Giza Governorate 12573, Egypt

3 MSA University ESE Department 6th Of October 12573 Egypt

4 NGU, First 6th of October, Giza Governorate 3296121, Egypt

Abstract

 Stroke is still the world's second biggest cause of mortality.
It is one of the illnesses that artificial intelligence (AI) can detect.
Early detection of an acute stroke is crucial for commencing
prompt treatments and reducing morbidity and death. Imaging
techniques such as (CT) Computed Tomography and (MRI)
Magnetic Resonance Imaging can identify it, however, they take
longer and have worse accuracy than AI. Artificial intelligence
algorithms are particularly adapted to the rapid decision-making
required in the management of big vessel occlusive strokes.
Through early categorization by CT and MRI, AI can assist in
identifying kinds of strokes such as ischemic and hemorrhagic
strokes. With the help of AI, doctors can quickly analyze a patient's
brain scan and receive results in minutes. Imaging is also important
since professionals may evaluate amounts of data and detect any
indicators of a possible stroke. AI enhances the quality of (CT) and
(MRI) scans, yielding more than 90% accuracy and improving
patient care. The AI detection time of a brain stroke is now 5
minutes. We will discuss the use of AI in stroke imaging and how to
improve (CT) and (MRI) quality in this study.

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MSA Engineering Journal
Volume 2, Issue 2 - Serial Number 6
Special issue for Artificial Intelligence & Sustainable Engineering Conference: A Path to The Future
March 2023
Pages 998-1021

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