Authors :
KANAGARAJ S; NAMITHA.V
Volume/Issue :
Volume 6 - 2021, Issue 11 - November
Google Scholar :
http://bitly.ws/gu88
Scribd :
https://bit.ly/3BUZ1sx
DOI :
https://doi.org/10.5281/zenodo.6299989
Abstract :
The algorithm in machine learning plays an
essential role in the identification of patterns in biomedical
sciences. For complex medical problems, there are many
classifications of medical images and forecasts of the
model. The neurological disease which largely attacks the
motor system are Parkinson Disease (PD). With the help of
a Magnetic Resonance Imaging (MRI) or any kind of scan
can be used which can detect and predict the disease. By
using the level of the dopamine, the PD is detected. This
paper presents an overview of various prediction and
detection techniques used to identify Parkinson disease.
The deep learning and machine learning algorithm are
compared here. The survey contains ANN, CNN and
neural network- based paper are compared. The different
strategies and algorithms in disease prediction and
detection are recognized and evaluated. The results and
principal issues of each study paper are discussed and
analysed in this paper.
Keywords :
Parkinson Disease (PD),CNN ,ANN ,Dopamine ,Neural Network, Deep Learning, Machine Learning.
The algorithm in machine learning plays an
essential role in the identification of patterns in biomedical
sciences. For complex medical problems, there are many
classifications of medical images and forecasts of the
model. The neurological disease which largely attacks the
motor system are Parkinson Disease (PD). With the help of
a Magnetic Resonance Imaging (MRI) or any kind of scan
can be used which can detect and predict the disease. By
using the level of the dopamine, the PD is detected. This
paper presents an overview of various prediction and
detection techniques used to identify Parkinson disease.
The deep learning and machine learning algorithm are
compared here. The survey contains ANN, CNN and
neural network- based paper are compared. The different
strategies and algorithms in disease prediction and
detection are recognized and evaluated. The results and
principal issues of each study paper are discussed and
analysed in this paper.
Keywords :
Parkinson Disease (PD),CNN ,ANN ,Dopamine ,Neural Network, Deep Learning, Machine Learning.
