Inspiration

With the growing popularity of web3 and decentralized apps, as well as growing awareness of possibilities for increased security, we decided to make a dApp for medical scans. Although there may be ways for patients to retrieve their medical imaging and diagnoses, current methodology uses email, fax, or phone call, all of which could be more secure.

What it does

Doctors on Dial is a secure blockchain based medical communication site. Doctors and patients can transfer medical data securely as well as utilize matlab's functions and our own ai model to analyze different medical conditions; at the moment doctors can use an ai model that can check for cancers in tissue, given different images of tissue and cells.

How we built it

Doctors on Dial is built with MatLabs, NEAR, and Javascript. We used Python and MatLabs for the backend, and Jupyter for the AI model. The smart contracts were developed with NEAR in Javascript and the frontend is a next.js web-app.

Challenges we ran into

This was our first time working with MatLab, as well as realizing the extent of its versatility. This was also our first time working with web3, and learning how to make smart contracts as well as finally understanding more about the concept of blockchain and web3 in general took a significant amount of time. However, with the help of NEAR documentation, we were able to figure it out!

Accomplishments that we’re proud of

We are proud of our ai model, which took some time to debug but ended up worth all the effort. Also, we can finally say that we know enough about web3 to build with it more and learn more about it! Getting smart contracts working and being able to deploy and see the transaction hashes was very satisfying, especially after long periods of debugging.

What’s next for Doctors on Dial

Due to time constraints, we were unable to implement AI upscaled images that would make diagnosis easier for doctors, as well as resolving the need to retake unclear medical images that would potentially take a significant portion of the patient’s time.