Prediction of Parkinson's disease through Automation using Machine Learning Algorithms

Prediction of Parkinson's disease through Automation using machine learning algorithms | A Automation Anywhere - 360

YouTube Link :: https://youtu.be/g6M7MxIzoBo

To predict Parkinson's disease through automation, machine learning algorithms can be trained using datasets that contain information about people with and without Parkinson's disease. The algorithms can then learn to identify patterns and relationships between different features such as motor symptoms, speech characteristics, and gait analysis. Some of the steps involved in predicting Parkinson's disease through automation are:

To predict Parkinson's disease using automation or machine learning, you can follow these general steps:

1. Data Collection: Collect a dataset consisting of relevant features or biomarkers associated with Parkinson's disease. This can include voice recordings, gait analysis, or other non-invasive measurements.

2. Data Preprocessing: Clean and preprocess the dataset to remove noise, missing values, and outliers.

3. Feature Selection: Select the most informative and relevant features or biomarkers from the dataset for use in the model.

4. Model Development: Develop a machine learning or deep learning model that can learn from the dataset and predict whether a patient has Parkinson's disease.

5. Model Evaluation: Evaluate the performance of the model using various metrics such as accuracy, sensitivity, specificity, and area under the curve.

6. Model Deployment: Deploy the model for clinical use in screening or early detection of Parkinson's disease.

Some machine learning algorithms that can be used for this task include logistic regression, decision trees, random forests, support vector machines, and artificial neural networks. It is important to note that these models are still in the research stage and have not yet been widely adopted for clinical use. The diagnosis of Parkinson's disease still requires a thorough evaluation by a medical professional. Refer to github repository for Prediction of Parkinson's Patients by using Data Analytics and Machine learning Github link : https://github.com/nkarun/Prediction-of-Parkinson-s-Patients-by-using-Data-Analytics-and-Machine-learning