Healthcare Web Portal for multiple disease diagnostic

Making diagnostic simpler and affordable for all

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Inspiration

Many people across our country are suffering from incurable medical conditions as a result of improper medical checkup, lack of timely diagnosis, over-dependency on doctors that charge a huge amount of money as consultancy fees, and lack of specialist doctors who can provide them with proper consultancy and treatment. The Idea is to come up with a healthcare web portal that could provide people with the facility to get a diagnosis of multiple diseases within a matter of seconds, thus not making the patient’s disease grow by wasting too much time on detection.

What it does

This will be achieved through a user-friendly website that facilitates multiple end-to-end disease detection model built using robust Machine Learning and Deep Learning model which are trained on data of thousands of patients diagnosed before from across the globe, by taking in inputs from the medical reports of the person we can predict whether that person is suffering from a disease or not.

How we built it

We built the machine learning and deep learning models using the datasets provided on platforms like kaggle, we then embedded the trained models onto a user friendly website that will take inputs from user, feed it onto the model, and provide him with the results.

Challenges we ran into

The major challenge that we faced was to find the data required to train the model, as healthcare is a sensitive field we needed to find data that is reliable enough to provide us with good diagnostic. Another major challenge was to get connected with specialist doctors, and get their feedback on the idea, and discussing with them on how we can improve the healthcare condition in our country

Accomplishments that we're proud of

This project is completely built on the basis of design thinking methodology involving: -Empathy Phase (Putting ourselves in customer shoes to understand the challenges they are facing) -Define: defining the problems they are facing -Ideate: brainstorming on ideas that could possibly solve the problem faced -Prototype: building upon the most promising Idea -Test: Validation our prototype

This prototype serves as an example on how we can leverage the power of AI in healthcare field for medical diagnostic

What we learned

-We learned how AI can help reduce time and resources needed to examing and diagnose patients -We also learned more about the problems that common people are facing in healthcare domain, both from the perspective of doctor and patient

What's next for Healthcare Web Portal for multiple disease diagnostic

Scaling the application, that involves training the models on larger dataset to bring more robustness in the application. getting the application validated from experts in the field of healthcare

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