HI, thanks and sorry for the late reply. I have been doing a bit of reading. Let's say I am up2date until more or less the date of your review (2007).
First, I wonder if something new come out since then (rather than evolutions of approaches/standards already existing). Second, I got the impression that rationales to standardize clinical trials criteria vary a lot. Mining EHRs for candidates has different requirements from criteria re-use, which in turns has different requirements from (trials) discovery. I was looking for some sampling of criteria in use in clinical trials. Could not find anything (at least open). Does anybody have some pointer in this direction ? best, Andrea Il giorno 15/lug/2013, alle ore 07:21, Kathrin Dentler <k.dent...@vu.nl> ha scritto: > Hi Andrea, > > For a first broad overview, this paper is a good starting point: > Formal representation of eligibility criteria: A literature review > http://www.sciencedirect.com/science/article/pii/S1532046409001592 > > For CDISC, there is ongoing work on OWL/RDF formats: > http://www.cancer.gov/cancertopics/cancerlibrary/terminologyresources/cdisc > http://kerfors.blogspot.nl/2012/05/semantic-models-for-cdisc-based.html > > Best, > Kathrin > > > > Op 7/15/13 1:34 AM, Andrea Splendiani schreef: >> Hi, >> >> I was wondering if somebody could provide some pointer to work going on in >> an area that is related to clinical trials: inclusion and exclusion criteria. >> (I have followed the recent thread on encoding Hamilton Disease and >> pointers). >> >> In, particular, I am interested in two things: >> Standards with substantial uptake (sub question: is CDISC's uptake actual or >> perspective ?). >> >> Modeling of inclusion/exclusion criteria, but with a particular twist: not >> modeling the questions, but the facts that are queried. Basically I am >> interested in modeling patients and conditions (to the level of detail >> required "usually" required by clinical trials). The subject itself can be >> very vast, but is there a framework which provides at least an upper >> perspective on how to model subjects's features, diseases, interventions, >> samples (also respect to time) ? >> >> Any pointer is welcome! >> >> best, >> Andrea Splendiani >> >> > > > -- > Kathrin Dentler > > AI Department | Department of Medical Informatics > Faculty of Sciences | Academic Medical Center > Vrije Universiteit | Universiteit van Amsterdam > k.dent...@vu.nl | k.dent...@amc.uva.nl > > http://www.few.vu.nl/~kdr250/ > >
