Carebookr- ideathon

Inspiration

We took inspiration from MyChart and the many other online booking softwares and applications. Although, MyChart has not been able to reach to most hospitals in the United States, especially urgent care centers.

What it does

Our product is a deep-learning trained AI that uses previous years of patient data to estimate the likelihood that a patient will have a certain disease. Based on the risk of the disease and its likelihood it will advise the patient on the right course of action, such as going to urgent care. If the patient chooses to go to urgent care, the AI will notify the doctor and save their information on the google cloud data base then send the doctors the patient’s data, and schedule a comfortable time for the patient to make the appointment, saving appointment and symptom data all in the storage space. This will then save time at the care in both waiting time and the pre-physical examination questions. This way, when the doctors did find something in the physical examination, and input the data, the AI can also check whether it matches the patient data or not.

Challenges we ran into

At first we had many disagreements with what topics we should pick, and what areas we should find a solution to, but we later tried to narrow our solutions to not go too broad, and mixed all of our ideas into a program that can upgrade safety and time.

Accomplishments that we're proud of

We are proud of the techniques we had to learn in order to make our final presentation. Thomas had to learn how to use a new program, and Hao had to use premier pro premiere pro to animate pngs due to after effects crashing every other second.

What we learned

Due to covid, a lot of hospitals are in worse shape than it seems at the surface. Being understaffed and overworked makes repercussions that affects many other areas that people face daily, but not realize the cause. Low healthcare personnel commitment burnout and stress both the patients and the workers with low quality of care and long appointment wait times.

What's next?

Making Carebookr into an actual model and application, distributing the use to millions of users across the united states, boosting the small issues that might make work-flow for everyone less complicated.

Built With

• clip-studio-paint
• google-docs
• krita
• lucidchart
• premiere-pro
• react-native