Inspiration
Human evolution is an intriguing process, with all the advancements in every field of life, the medical industry has also seen a vast influx of new technologies that help to treat diseases efficiently. But the major problem these days is the affordability of treatment and medicines. With more than half of the world's population living with minimum wages and with about one billion people below the poverty line, the cost of medicine and treatment plays a very big role.
What it does
The project we are integrating will take symptoms as input and predicts the disease that is most likely susceptible by the user.
How we built it
The project is built with the help of Google collab(python), HTML, CSS, Flask, Heroku.
Challenges we ran into
Initially, we faced some issues with the accuracy rate of the machine-learning model, but we successfully overcame them late on. One of the major challenges we faced during this project is when we were integrating the project using Flask, where the algorithm did not run due to some errors.
Accomplishments that we're proud of
In this project, according to our opinion, our approach to the problem statement is unique and can be implemented in the real-world industry. The disease prediction model can predict the diseases the patient is suffering with good accuracy and can result in saving a considerable amount of time and resources for the user.
What we learned
We learned about the medical industry and its functionalities with different technologies. we also learned some major concepts like integrating the project with high efficiency and we learned the framework Flask.
What's next for Project MedicAid
This project can be improved further and can be launched as a service provider app for the public.
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