My father and I are frequent blood donators. At our most recent donation, one of the nurses mentioned a shortage of blood and how much blood hospitals actually waste. This really intrigued me, and I wanted to learn further about it. I uncovered that the blood loss crisis is a huge deal, and I wanted to help somehow. I thought to myself, is there a way I can try and solve this issue or try to decrease it. When we were first introduced to machine learning and its benefits, I knew we could implement it and optimize it. The rest of the group agreed that it was a fantastic idea, and since we were all on board, we went ahead with it, hoping to make a difference in the world.
What it does
Our algorithm will be able to solve two problems at once. It will optimize the hospital and reduce wastage of blood and resources. It will predict the amount of blood needed on a daily basis and in the future. It will also lead to saving countless lives.
How we built it
We used a four-step process to create the algorithm. First and foremost, we need Hospitals and Blood banks to input their usage and past statistics into our database. Next, our website stores all the information from multiple facilities. The algorithm considers numerous parameters such as past statistics, weather, schedule and organizes it using regression analysis. Based on our algorithm, machine learning inputs, and the data, we can predict the blood required each day at the hospital. Finally, the hospital can optimize its system and order blood-based on the algorithm to minimize wastage of essential resources that can save countless lives.
Challenges we ran into
We ran into some challenges while trying to create an algorithm and get the ball rolling was a data set, and it wasn't easy to come across a data set, so we ended up creating an artificial one based on some statistics and research.
Accomplishments that we're proud of
We ended up creating an artificial data set based on some statistics and research. We also created the app and developed a program to deploy to optimize hospitals and help save lives.
What we learned
We learned how to build an algorithm, machine learning inputs, and create artificial data based on statistics and basic research. We also learned how to do basic optimization and coding in R.
What's next for A Cybernetic Solution to Optimize Blood Allocation
The next steps for A Cybernetic Solution to Optimize Blood Allocation are developing a more advanced algorithm that considers much more parameters and is more effective and efficient. After that, I believe we should deploy the software to minimize the wastage of blood and help save lives.