The project that I
am currently working on involves measuring iron accumulation and brain atrophy
in patients with multiple sclerosis with the use of MRI technology. I am an
aspiring radiologist, so the first thing that really peaked my interest was the
idea of being able to work with MRI images and medical imaging tools. After
further reading about the project and meeting my mentor, I was able to
understand how important this project was going to be in the multiple sclerosis
(MS) field. There is currently no cure for MS, so any information regarding
different aspects of the disease is essential. Not only was this going to be an
amazing opportunity to be able to work on, but I also knew that I was going to
learn a lot considering I only possessed basic knowledge of MS and MRI
technology at the time.
This project is
very much related to my long-term goal because I want to become a radiologist
and ultimately analyze medical images for a living. There are a variety of
different areas to specialize in within the field of radiology, so being able
to work with neurology now (and hopefully other areas later on) will help me
narrow down what parts of the body I am most passionate about.
I do a lot of
similar work from week to week. My mentor and I try to meet once a week and in
these meetings we will discuss what is going on with the project right now and
then we will analyze an article together and see what type of research others
are doing with MS and whether there is other evidence out there to prove what
we are doing is headed in the right direction. What I do on a weekly basis has
changed since I started this project, but right now I mainly have been working
with the data and am trying to find some statistical significances between
different variables. We are trying to find correlations between a few of the
key aspects involved in MS. This involves trying to figure out which set of
data will be the best to use and then running various statistical tests, like
one and two sample t-tests, spearman correlations, pearson correlations, etc. Once
the tests are run, I analyze the numbers, see if there is any significance, and
whether there is significance or not, I have to ask myself what exactly does
this mean for the data?
One thing that I
have learned this week is the correct way to run spearman correlations in R
Studio! (Statistical software.)
