Apna CheckUp

Inspiration

Because of COVID, it is now unsafe to go to the hospital every time we feel ill since there is a risk of getting affected with COVID in the hospital. Thus there is a need to connect patients virtually with doctors. Also if the patient recognizes his/her symptoms, and if somehow we can tell him what is the disease he is likely to be affected with then he/she can take precautions accordingly. We believe that everyone should have easy access to great health care.

What it does

We have designed a CAD system/Disease Prediction system where users can get to know whether they are infected with a particular disease or not based on the input in the form of report or X-Ray/MRI Image. Not only this, but our project also aims to effectively connect doctors and patients virtually around the globe and incase if a patient recognizes the symptoms, then he/she can know what disease he/she is likely to be infected with and what precautionary measures can be taken.

How we built it

We used scikit-learn for training machine learning models while tensorflow/pytorch for deep learning and segmentation models. Dataset was obtained from kaggle website. A model was trained to predict the disease based on the user's symptoms. Sqlite database was used to store data of doctors around the world and the user can search doctors based on location or specialization, request for a video meeting and then discuss his/her problems.

Challenges we ran into

Connect patients with doctors in real-time. Improving the accuracy of ML/DL models.

Accomplishments that we're proud of

Although our application is not fully functional, we have designed a decent prototype which very well meets the requirements of our plan of actions. All the models trained have a accuracy of more than 95%. Fast redressal of grievances of patients from doctors in real time

What we learned

Reduce the gap between patients and doctor.

What's next for Apna CheckUp

Built With

• aws-transcribe
• bootstrap
• dailyjs
• deep-learning
• django
• html5
• javascript
• keras
• machine-learning
• materialize-css
• python
• pytorch
• scikit-learn
• sqlite