Glossary

Healthcare in 3D Terms and Phrases

  • Dimension — The reference to “dimensions” in the name Healthcare in 3D (3 Dimensions) is not just a catchy marketing phrase, but also a clever reference to the 3 types (or context) of dimensional concepts ubiquitous to HCn3D: spatial, statistical, and stratified.
  • Dimension (spatial) — In the context of “spatial” dimension refers to the sides of the “cube” which is 3 dimensional. Provider Logic, measure, and Time Intervals.
  • Dimension (statistics) — In the context of “statistics” (data) dimension refers to structures or attributes that categorize measurements or metrics. For instance systolic would categorize the "top" number in a patient's blood pressure.
  • Dimension (strata) — In the context of “strata” dimension refers to layers. Most commonly the multilevel hierarchal layers of the healthcare network.
  • Dimension Reduction — Is the process of reducing the number of variables under consideration to a manageable and useful number of independent features. 100s if not 1000s of individual pieces of data (dimensions) may be relevant to a Provider Action at the Inflection Point. A very simple example of Dimension reductions can be demonstrated in the categorization of blood pressure. Systolic and diastolic are what data scientists would call Natural Features and they could be used directly to Train a model, but by Feature Engineering a third dimension that categorizes the measurement into a list of 3 Factors: “Normal”, “hypotensive”, and “hypertensive” the processing and possibly even predictive performance is improved. This is also a good example of Feature Engineering to improve the ability to understand the data, since knowing a patient simply has Hypertension is more intuitive than reading the actual mm of Hg.
  • High dimensional — Having the property of a higher level of the network.
  • High Dimensionality — In the context of HCn3D analysis, it is simply data instances (records) with the potential to comprise many variables (columns), potentially more variables that there are records being analyzed (e.g. Electronic Medical Record).
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