BioMedical Data - A Sea to Explore
This blog is just an overview of what I think of how Bio Medical Data can be explored and how can use Machine Learning to get some useful insights out of it.
Y = MX + C
The above equation is a linear equation, what are your thoughts when you see this equation. In every Machine learning class or “A.I” class, maybe the main focus is on M and C but the crucial part is X - DATA. Most of the biomedical data contains the direct information for eg. Have a look at the ECG signal.
Reading the Signals
All details are present in the few data points on the left and right of R or the peak in the above figure 1. It’s not necessary to be a cardiologist; we just need the data points.
As these raw data points make up the information, I made use of it for preparing a feed-forward network using MATLAB (ANN). As a beginner, I made use of this raw data for detecting the disease patterns.
I knew nothing about the preprocessing & data science at all. But however I knew only one thing, differentiating factors, different patterns possess distinct data-points.
Lets check some of the examples:
Visually the differences can be plotted; such data points can be directly fed to the Neural Networks for classification. This helped me get started into the importance of data and Data Science.
Here's a paper I have written detect various patterns using neural network