http://rahulpatil35.pythonanywhere.com/
Explanation of ML Model August 20, 2021 by Rahul
Project link : http://rahulpatil35.pythonanywhere.com
The "goal" of this project is to find the presence of heart disease in the patient.
Logistic Regression Logistic regression is a supervised learning classification algorithm used to predict the probability of a target variable. The nature of target or dependent variable is dichotomous, which means there would be only two possible classes. Mathematically, a logistic regression model predicts P(Y=1) as a function of X
Features & Target
Features list • age • sex • chest pain type (4 values) • resting blood pressure • serum cholesterol in mg/dl • fasting blood sugar > 120 mg/dl • resting electrocardiographic results (values 0,1,2) • maximum heart rate achieved • exercise induced angina • oldpeak = ST depression induced by exercise relative to rest • the slope of the peak exercise ST segment • number of major vessels (0-3) coloured by fluoroscopy • thal (4 values) Target list • result (values 0,1 | 0: heart disease not present, 1: heart disease present)
This is a definition list:
Features A feature is a measurable property of the object you’re trying to analyse. In datasets, features appear as columns. Target The target variable of a dataset is the feature of a dataset about which you want to gain a deeper understanding.
Libraries & Packages pandas, sci-kit learn, matplotlib, numpy, os, pickle, flask, flask_mail, sqlite3
Validations Validation is the process of checking whether the given input/product is up to the mark.. • Age - 10 to 130 • Blood Pressure - 80 to 200 • Cholesterol - 100 to 600 • Heart Rate - 70 to 210 • Oldpeak - 0.0 to 6.0
Future Scope
- Model can be made more accurate using more attributes and/or more amount of data
- API of the project can be made which can be used directly by Third-Party Applications.
- Separate Admin Panel and Dashboard for Medical Staff and Users can be implemented
- Passwords can be encrypted before they are stored in Database.
- Nearest Hospital Locations can be displayed using Geo-location and Google Maps API
Contact: Email : [email protected] Phone : (+91)8308009372 LinkedIn : rahulpatil35 GitHub : rahul3355