| dc.description.abstract | The space of clinical planning requires a complex arrangement of information, often not
capable of being captured in a singular dataset. As a result, data fusion techniques can be
used to combine multiple data sources as a method of enriching data to mimic and
compliment the nature of clinical planning. These techniques are capable of aiding
healthcare providers to produce higher quality clinical plans and better progression
monitoring techniques. Clinical planning and monitoring are important facets of
healthcare which are essential to improving the prognosis and quality of life of patients
with chronic and debilitating conditions such as COPD. To exemplify this concept, we
utilize a Node-Red-based clinical planning and monitoring too that combines data fusion
techniques using the JDL Model for data fusion and a domain specific language which
features a self-organizing abstract syntax tree. | en_US |
