Health information applications involve processing of large amounts of data. Similarly, a biomedical tool also senses, collects, and processes numerous data points and, to a good extent, even processes those data.

Algorithms advise an optimal method to process or analyze a given set of data in the required manner. For example there are several algorithms to 'sort' a given set of data (two examples, bubble sort and SyncSort). Often, when there are multiple processing  steps, more than one algorithms are used to achieve the desired goal. E.g. to group a given large data set, it needs to be sorted and optimally grouped. One may use an optimized sort algorithm and then use specific grouping algorithm to get an optimally grouped (or categorized) data.

Study of algorithms informs one about systematic and optimal steps of achieving the desired results. If one devises his / her own steps to achieve required outcome, that becomes an algorithm. The 'devised' algorithm  may be better or worse than the already existing algorithms (if any) that give the same outcome.