Automatically detecting interactions between medication rules for elderly patients

From Master Projects
Jump to: navigation, search


About Automatically detecting interactions between medication rules for elderly patients

  • This project has not yet been fulfilled.
  • This project fits in the following Bachelor programs: {{#arraymap:|, |xXx|bachelorproject within::xXx|,}}
  • This project fits in the following masterareas: {{#arraymap:Human Ambience, Technical Artificial Intelligence, Knowledge Technology and Intelligent Internet Applications|, |xXx|project within::xXx|,}}


Description

GOAL Interactions between guidelines is an increasing problem in a increasingly elderly population, with increasing prevalence of comorbidities. It is currently difficult to detect such interactions because guidelines are written independently from each other.

In this project, we will test a method for semi-automatic detection of guideline-interactions in the domain of medication for elderly patients.

MATERIALS

RESULTS Measures of precision and (if possible) recall on identified interactions between medical decision rules on medication for elderly patients.

METHOD

1. reformulate MedLock's formalisation of the ACOVE-NLI subset inZamborlini's TMR-i model

2. implement the resulting model in computer-executabe form

3. use the resulting implementation to infer possible guideline interactions

4. validate the detected interactions with a domain expert on soundness (precision) and completeness (recall).

STAFF INVOLVED

  • MedLock from KIK,
  • Veruska Zamborlini & Annette ten Teije from KRR@VU,
  • Andrea Maier from VUmc.