Authors :
Sai Chandan P Reddy
Volume/Issue :
Volume 6 - 2021, Issue 11 - November
Google Scholar :
http://bitly.ws/gu88
Scribd :
https://bit.ly/32pQvUE
Abstract :
Stroke is the second leading cause of mortality
worldwide, and it continues to be a huge health burden for
both individuals and national healthcare systems.
Hypertension, cardiac disease, diabetes, dysregulation of
glucose metabolism, atrial fibrillation, and lifestyle factors
are all potentially modifiable risk factors for stroke. Stroke
is a life-threatening medical condition. When blood flow to
a portion of your brain is halted or diminished, brain
tissue is deprived of oxygen and nutrients, resulting in a
stroke. Within minutes, brain cells begin to die. The
authors aimed to derive a model equation for developing a
stroke pre-diagnosis algorithm with the potentially
modifiable risk factors. Ischemic embolic and
haemorrhagic strokes account for the bulk of strokes.
When a blood clot forms far away from the patient's brain,
usually in the heart, it travels through the circulation and
lodges in the patient's smaller brain arteries.
Haemorrhagic stroke is another type of brain stroke that
happens when a blood vessel in the brain ruptures or spills
blood. Stroke is the world's second leading cause of death
and one of the leading causes of death in persons over the
age of 65[1]. By the method proposed, it would be able to
mitigate the stroke by 99 percent, which is almost most of
the time.
Keywords :
Stroke prediction system, Artificial neural network, deep learning, prediction system, accuracy.
Stroke is the second leading cause of mortality
worldwide, and it continues to be a huge health burden for
both individuals and national healthcare systems.
Hypertension, cardiac disease, diabetes, dysregulation of
glucose metabolism, atrial fibrillation, and lifestyle factors
are all potentially modifiable risk factors for stroke. Stroke
is a life-threatening medical condition. When blood flow to
a portion of your brain is halted or diminished, brain
tissue is deprived of oxygen and nutrients, resulting in a
stroke. Within minutes, brain cells begin to die. The
authors aimed to derive a model equation for developing a
stroke pre-diagnosis algorithm with the potentially
modifiable risk factors. Ischemic embolic and
haemorrhagic strokes account for the bulk of strokes.
When a blood clot forms far away from the patient's brain,
usually in the heart, it travels through the circulation and
lodges in the patient's smaller brain arteries.
Haemorrhagic stroke is another type of brain stroke that
happens when a blood vessel in the brain ruptures or spills
blood. Stroke is the world's second leading cause of death
and one of the leading causes of death in persons over the
age of 65[1]. By the method proposed, it would be able to
mitigate the stroke by 99 percent, which is almost most of
the time.
Keywords :
Stroke prediction system, Artificial neural network, deep learning, prediction system, accuracy.
