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Predictive analytics

Analytics in Realu00a0Lifeu00a0<br><br>When you generally think about words like data, analytics, and analysis it is very easy to visualize big computers, engineers, or even bankers- you wouldn't imagine a doctor. Sorry if the previous statement sounded a little presumptuous to me, but it needed to be used as it would set a good opening for this blog. Today as a part of analytics in real life we will attempt to take a closer look at analytics from a medical perspective.

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Predictive analytics

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  1. Predictive analytics Probably one of the most important models in the medical field, predictive analytics based on the electronic health record system can be used from clinical prediction to treatment outcomes. The clinical prediction uses a large set of data to predict what conditions the patient is likely to develop based on multiple sets of data and regression. Predictive analytics is also used for understanding disease progression and comorbidities. This article is quite a great read on this subject. This article though lengthy is a great read on the subject of the history of predictive analytics in the medical field, give it a read it is quite interesting. https://gigrich.net/analytics-in-real-life/

  2. R-value The use of data in medical research is probably the most critical function in analytics. This ranges from establishing what are acceptable ranges for key blood parameters to identify the pattern in the spread of viruses- a recent conversation about the R-value of Covid is one such example. The collection of data and its use in medical science can be the subject of many exciting blogs. So let’s look at some examples of what are some of the most common data models used in medical science: https://gigrich.net/analytics-in-real-life/

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