Alzheimer’s is still a very new and under researched disease so we still do not quite have all the information about it. My objective is to find current ways to detect this disease therefore we could save more people from it. The main problem I would like to address with my project is how can we use our technological advancements to detect what stage of this disease someone might have.

The method that I will be using is machine learning (ML) using python on google collab notebook. I have never used a coding notebook like this so it was quite a challenge. The idea was to create a code that would use an algorithm that compares MRI (Magnetic Resonance Imaging) scans of the brain with others to check for differences, depending on what my code finds, it will tell you how many of the images has either mild or severe Alzheimer's. So far for my code I got all the images to load, and it augments them to make them more readable.

This is an attempt at using our current technological knowledge to analyze MRI scans of the brain and find a way to detect it sooner for people who are concerned and potentially find a way to treat it in the early stages. For my code, with each time that the images got compared, the accuracy level went up.

I would like to determine the effectiveness of this project on detecting the stage of Alzheimer's because I would like to make a change in the way we use our knowledge on technology to find ways to catch people in the early diseases and treat them in the early stages.

Centers for Disease Control and Prevention. (2020, October 26). What is alzheimer’s disease? Centers for Disease Control and Prevention. https://www.cdc.gov/aging/aginginfo/alzheimers.htm

All other info that I have about Alzheimer's came from Lynn Gordon.

I would like to give Lynn Gordon from Father Lacombe Care Center, and Cathal Smyth, a data scientist from Toronto a huge thank you for making an impact on my project. I would also like to thank Tim Gubski and Irada Shamillova.