In the recent times of COVID, hospitals & doctors are very busy with the increasing umber of patients suffering from COVID. In such times we must try to avoid going to hospitals unless absolutely necessary.
Thus, we have tried to build a website where one can select the symptoms he/she is facing and accordingly the system shall predict a certain disease or condition he/she might be suffering from. Along with it, certain solutions as to how he/she can overcome that disease/condition will be given which will help them to fight against the problem without actually going to a hospital or doctor. Further we also have a page where the user can select the city and disease and the system will display certain hospitals where treatment is available for those diseases.
Initially we looked for datasets which had the different symptoms and the diseases related to it. Then we applied various machine learning algorithms to train our models based on this dataset. So using these models we were able to predict the possible disease or condition based on the symptoms selected. Then we started to build a web application on local server using Flask and Python. Then we also worked with HTML and CSS to create the different web pages.
Backend configuration regarding linking our web application to a database system.
We are proud of the fact that if produced properly, this project can prove to be helpful for people during these tough times of COVID by not creating confusion and commotion at hospitals and instead give them helpful solutions in time as well.
Through this project we were able to learn how to apply basic machine learning algorithms to make predictions. Then we learnt how to actually integrate these algorithms into a web application to make it interactive. Along with this, we also improved our HTML and CSS skills required for web development.
Trying to link the web application with a database system and also trying to improve on the machine learning algorithms. With more data or more correct information we will be able to make the entire system much more accurate and trustworthy.
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