Several studies have shown that doctors would be able to make better and more effective treament plans for patients if doctors were able to understand how a patient really feels. For patients with severe illnesses and problems like those who suffer from depression and alzheimers, doctors usually have to assume how the patient is feeling on certain days which can lead to problems.
What it does
Kenko uses machine learning and AI to detect and analyze the semantics of journal entries and then convert the text into metrics that can be used by the doctor to make better and more specialized plans on the next steps for the patient. It has been proven that journalism is a great way to get rid of your emotions, so Kenko aims to redefine the healthcare industry by using a neural network to analyze the emotions. This can be used by all healthcare providers and can make a huge difference
How I built it
To build the frontend, I used html css as well as js and php which I learned from this hackathon For the backend, I used flask. This was my first time using flask as a database to keep and store values and update reatlime rather than using firebase to store data. I used python to build the sentiment analysis algorithm that was used to understand the semantics CanvasJS and Python was used to keep track of the emotions, and add the scores in the advanced analytics (graphs page).
Challenges I ran into
Accomplishments that I'm proud of
I am proud of creating a sentiment analysis model in such less time (100% accuracy) Proud of using Canvas JS for the first time and making a flask database which I hope to encrypt for user privacy First time writing over 1000 lines.
## What I learned Learned about deeper machine learning models, CanvasJS, and other important concepts such as blockchain from the workshops that I hope to implement in the database that will store all the patients.
What's next for Kenko
I would like to try and promote this in a healthcare home or a reitrement home as well as a healthcare center. This would have a great impact on the communitydev