An ontology is a model of some part of the nursing domain. It can categorise things and infer new knowledge using an inbuilt 'reasoner'.
this is a simple artificial intelligence demonstration using a reasoner and OWL-DL ontology.
Enter the synthetic patient's data below. That is, select a patient, enter their age and 6 acuity scores.
Acuity scores measure how well (or poorly) a patient is faring in various areas of function.
The scores range from 0 (great) to 16 (very concerning).
Basically, the reasoner/ontology uses your information to categorise a patient into acuity classes and infer treatment and suggestions.
Including the best nurse to care for the patient and the best ward. It also flags caution for patients in a 'grey area' of care.
Input

Select a patient


Enter the patient's age in years------->

The acuity scores (0-16)
0-4 minimum, 5-8 medium, 9-12 high, 13-16 maximum

Airway breathing and circulation score->

The impact of symptoms score----------->

The amount of supervision score-------->

Feeding score-------------------------->

Hygiene and toileting score------------>

Mobility score------------------------->

Here is a concept map of the above application.