Guergana, thank you. Is there anything in cTAKES now for walking the UMLS ontology (e.g. for finding hypernyms, synonyms, etc.)?
Dima > On Feb 15, 2017, at 12:45, Savova, Guergana > <guergana.sav...@childrens.harvard.edu> wrote: > > Hi Erin, > Yes, creating your customized dictionary is the way to go. You can prune by > semantic types of interest and then remove branches that are not relevant to > your specific phenotype. I am not aware of cTAKES implementing such a tool > for a very customized dictionary. > > You can also start with a few terms that you know are relevant to your > phenotype and then find their synonyms in the UMLS. Then, you can further > walk a specific ontology and take siblings, parents if you think they are > relevant. > > Then, there is the whole field of using word embeddings to find > synonyms/related terms from unlabeled data if you want to become really > fancy :-) At this point, cTAKES does not implement any deep learning > algorithms, in the future we are planning to release a bridge to KERAS. > > I hope this makes sense. > > -- > Guergana Savova, PhD, FACMI > Associate Professor > PI Natural Language Processing Lab > Boston Children's Hospital and Harvard Medical School > 300 Longwood Avenue > Mailstop: BCH3092 > Enders 144.1 > Boston, MA 02115 > Tel: (617) 919-2972 > Fax: (617) 730-0817 > guergana.sav...@childrens.harvard.edu > Harvard Scholar: http://scholar.harvard.edu/guergana_k_savova/biocv > ctakes.apache.org > thyme.healthnlp.org > cancer.healthnlp.org > share.healthnlp.org > > > -----Original Message----- > From: Erin Nicole Gustafson [mailto:erin.gustaf...@northwestern.edu] > Sent: Wednesday, February 15, 2017 1:38 PM > To: dev@ctakes.apache.org > Subject: Phenotype-specific entities > > Hi all, > > I would like to be able to only identify entities that are relevant for some > specific phenotype. One step towards achieving this would be to build a > custom dictionary with a limited set of semantic types. However, this is not > quite specific enough to only identify mentions related to one disease while > ignoring those related to some other disease, for example. > > Does cTAKES currently have a way to do this sort of filtering? Or, has anyone > developed their own tools that they'd be willing to share? > > Thanks, > Erin
