a
set of dispersion measures is calculated and combined with
frailty risk factors from the patient record,
creating specific objects called instances.
When a new elder comes, a new
instance is created. All instances are stored in an instance
stack. Initially, this stack of instances is formed by a set of
reference items. From the comparison between instances,
the system establishes different affinity degrees to create an
affinity tree with a subset of them, taking into account
several parameters. Finally, the interpretation of this
affinity tree is used to provide a frailty diagnosis in a more
accurate and practical way. In our case, frailty assessment
is based on objective comparison methods because today it
is not an absolute measure.
Next steps in our research include the formalization of
final results on the mobile screen to facilitate its interpretation
by the specialist. Also, we are studying the behavior
of the system with a larger group of elderly patients. And
the level of objectivity is provided in relation to other
systems.
Acknowledgments This work has been financed by the TIN2010-
20510-C04-04 project from the Ministerio de Ciencia e Innovacio´n
(Spain).