NDLI: Parkinson's Disease Detection Using Voice Measurements

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Parkinson's Disease Detection Using Voice Measurements

Content Provider	Scilit
Author	Patra, Raj Kumar Gupta, Akanksha Joel, Maguluri Sudeep Jain, Swati
Copyright Year	2020
Description	Parkinson's Disease is a dynamic condition of the central nervous system (CNS) characterized by muscle stiffness, tremors and alternations in speech and gait. It has five phases and affects several million people each year in India. The incidence of Parkinson's Disease (PD) is increasing and there is no sign of cure. PD is a neuro-degenerative condition influencing the hormone dopamine's ability to create neurons in the cerebrum. XGBoost is a Machine Learning algorithm known for for velocity and ease of implementation. XGBoost signifies extreme Gradient Boosting and depends upon decision trees. In listed task, we import XGB Classifier from XGBoost library, which is a usage of scikit learning APIs for XGBoost arrangement. The model is assembled to precisely detect the presence of Parkinson's syndrome in an individual. In this Python AI venture, utilizing the Python libraries scikit learn, XGBoost, pandas and NumPy, we assemble models utilizing a XGB Classifier. We will stack the information, get the highlights and names, scale the highlights, at that point split the dataset, construct a XGB Classifier, and afterward ascertain the exactness of our model. Book Name: Artificial Intelligence and Machine Learning in 2D/3D Medical Image Processing
Related Links	https://api.taylorfrancis.com/content/chapters/edit/download?identifierName=doi&identifierValue=10.1201/9780429354526-10&type=chapterpdf
Ending Page	158
Page Count	16
Starting Page	143
DOI	10.1201/9780429354526-10
Language	English
Publisher	Informa UK Limited
Publisher Date	2020-12-17
Access Restriction	Open
Subject Keyword	Book Name: Artificial Intelligence and Machine Learning in 2d/3d Medical Image Processing Visual and Performing Arts Parkinson Xgb Classifier Python Library Scikit Model Xgboost Extreme
Content Type	Text
Resource Type	Chapter

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