Big Data in Medicine

Big data has been the new tendency in many areas of study, including medicine. The three major steps of actually using all of the data provided by patients are:

1. Data extraction where the data of many individuals is collected, this includes body scans, body fluid samples, doctor visits, diagnostics, among other data
2. Data transformation which gets all of the previously collected data and puts them in the same format, for example it is no possible to compare directly an MRI scan with a blood sample
3. Data loading and interpretation which takes all the transformed data and makes analysis of it to make predictions of whatever it is that is being looked for.

An example of data interpretation is Google’s “flu trends” which can track a flue epidemic with real time data. A few years back it was not possible to track epidemics since the information was not provided continuously and by the time it could be interpreted it was over.

As we can see in the image below big data and all of its components are increasing significantly in order for big data to be relevant. 3 of the main aspects of big data, which can be seen in the image below, are:

1. Data Velocity which was previously given periodically is now being collected in real time
2. Data Volume: Since each digital image is about 20MB the amount of data increases quite quickly having an annual growth 1.2–2.4 exabytes (10¹⁸)
3. Data Variety, which has also evolved sine storing information has reduced significantly in cost and makes it easier to store videos instead of just images.

Reference:

http://www.ppc-journal.com/article/S1058-9813(16)30078-9/fulltext?rss=yes