Overview / Usage

Inspiration

Inspired by my Stage IV cancer journey and the passion to save as many lives as possible from cancer

What it does

Global ecosystem to fund precision medicine and empower patient data sovereignty with blockchain and AI

What's next for IasoCoin

Continue building the team and product, our Declaration: by 2018, 1 million cancer patients lives will be saved with precision medicine recommended by IasoCoin.

Methodology / Approach

How we built it

We first fetched the EHR(electronic health resources) information of the cancer patient from Athena using the API provided by Redox.
We then combined the EHR data with genetic data we grabbed from kaggle (https://www.kaggle.com/c/msk-redefining-cancer-treatment#description).
We run some machine learning algorithm on powerful Intel® AI DevCloud to train a model that is able to predict the mutation category and then we are able to apply precision medicine to that person.(The details of the genetic dataset can be found on kaggle)

Finally, we send the summary of the cancer patient our system generate back to athena.
This is only a prototype of our entire system. Once the real genetic dataset and personal profile of the cancer patient is available, our system will be able to provide the true precision medicine.

Challenges we ran into

Find suitable genetic dataset.
Use the provided API in a proper way.

Accomplishments that we're proud of

Fetch the EHR(electronic health resources) of a patient from hospital
Implement precision medicine using machine learning algorithm
Send Back the summary the of patient in PDF form.

What we learned

Teamwork, how to define needs and business case, how to find suitable dataset for your needs, and collaborate with the Redox, Athena, and Intel API tech support on site.

Technologies Used

redox, athena, intel-ai, Logistic Regression. Natural language process. Statistic Learning. python. gensim. keras. sklearn

Repository

https://github.com/shichence/stanford-hackathon-IasoCoin