- From: Kavitha Srinivas <ksrinivs@gmail.com>
- Date: Wed, 12 Sep 2007 11:06:57 -0400
- To: "Kashyap, Vipul" <VKASHYAP1@PARTNERS.ORG>
- Cc: wangxiao@musc.edu, Alan Ruttenberg <alanruttenberg@gmail.com>, "Andersson, Bo H" <Bo.H.Andersson@astrazeneca.com>, Landen Bain <lbain@topsailtech.com>, Rachel Richesson <Rachel.Richesson@epi.usf.edu>, public-semweb-lifesci hcls <public-semweb-lifesci@w3.org>, public-hcls-dse@w3.org, Stanley Huff <Stan.Huff@intermountainmail.org>, Yan Heras <Yan.Heras@intermountainmail.org>, "Oniki, Tom (GE Healthcare, consultant)" <Tom.Oniki@ge.com>, Joey Coyle <joey@xcoyle.com>, "Bron W. Kisler" <bkisler@earthlink.net>, Ida Sim <sim@medicine.ucsf.edu>
1. Yes, as Chintan said, in the case where you had explicit negations in the data (e.g., the lab data rules out the presence of a certain infectious agent), you clearly want to use open world reasoning. However, if someone is not explicitly asserted to be on some prescription drug, it is fair to assume that they are not taking the drug (closed world assumption). 2. I tend to think this comes from an understanding of the domain (unfortunately), and what you are modeling rather than the data characteristics per se. 3. There is some elegant work by Boris Motik and others which has addressed the issue of combining the two although I don't know what the status is on implementation. (http://www.webont.org/owled/2005/ sub12.pdf). In terms of whether you can do this using SQL querying alone, based on our experience, its unlikely. The problem is that the types of clinical exclusion and inclusion criteria we saw on clinicalTrials.gov cannot be easily reduced to SQL querying (at least with the structured medical records we got from Columbia). From discussions with other institutions, we know this isn't unique to Columbia (i.e., there is a substantial "semantic gap" between what's in the structured record and what is being queried by investigators for clinical trials). Kavitha IBM Research On Sep 12, 2007, at 9:14 AM, Kashyap, Vipul wrote: >> Agree. The assumption is that the user will choose whether it is >> closed world or open world. The key point that we've observed in >> terms of our clinical trials matching work using ontologies is that >> you need BOTH options to be available to correctly translate the >> exclusion criteria into DL queries. > > [VK] The key issues we may want to explore in the context of a well > defined use > case (which hopefully mirrors the real world to a significant > extent) are: > 1. How do we decide when to use OWA vs CWA? > 2. Is it possible to look at the data characteristics to determine > that? For > instance, Chintan's lab example where negative statements are > explicitly > asserted. > 3. Use of appropriate technology for the same. For instance, we may > want to > articulate the pros and cons of using a SQL querying based approach > as opposed > to an OWL classification based approach. > > ---Vipul > > > The information transmitted in this electronic communication is > intended only for the person or entity to whom it is addressed and > may contain confidential and/or privileged material. Any review, > retransmission, dissemination or other use of or taking of any > action in reliance upon this information by persons or entities > other than the intended recipient is prohibited. If you received > this information in error, please contact the Compliance HelpLine > at 800-856-1983 and properly dispose of this information.
Received on Wednesday, 12 September 2007 15:17:44 UTC