DESCRIPTION
The patent disclosure covers System and Method for COVID-191dentifier Using Smlt and Data Science.
The goal is to develop a machine learning model for Covid Disease Prediction, to potentially replace the
updatable supervised machine learning classification models by predicting results in the form of best
accuracy by comparing supervised algorithm.
Exploration data analysis of variable identification
• Loading the given dataset
• Import required libraries packages
• Analyze the general properties
• Find duplicate and missing values
• Checking unique and count values U Uni-variate data analysis
• Rename, add data and drop the data
• To specify data type U Exploration data analysis of bi-variate and multi-variate
Plot d1agram of pa1rplo!, heatmap, bar chart and Histogram U Method of Outlier detection With feature
engineering
• Pre-processing the given dataset
• Splitting the test and training dataset
• Comparing the Decision tree and Logistic regression model and random forest etc.
Here the scope of the patent is that integration of clinical decision support with computer-based patient
records could reduce medical errors, enhance patient safety, decrease unwanted practice variation, and
improve patient outcome. This suggestion is promising as data modelling and analysis tools, e.g., data
mining, have the potential to generate a knowledge rich environment which can help to significantly improve
the quality of clinical decisions.
5. CLAIMS
1/We Claim,
1. The patent disclosure covers System and Method for COVID-19 Identifier Using Smlt and Data
Science as described above in Fig 1 to 3.
2. The analytical process started from data cleaning and processing, missing value, exploratory
analysis and finally model building and evaluation.
3. The best accuracy on public test set is higher accuracy score will be find out. This application can
help to find the Prediction of Covid Disease.
4. Covid Disease prediction to connect with Cloud.
5. To optimize the work to implement in Artificial Intelligence environment.