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From "Savova, Guergana" <Guergana.Sav...@childrens.harvard.edu>
Subject RE: Phenotype-specific entities
Date Wed, 15 Feb 2017 18:54:03 GMT
I don't believe there is a tool for walking the UMLS ontology, Dima. But Sean should confirm
that his dictionary building tool does not have that functionality.

I think you can use the UMLS tables to get that information. It has been quite a while I have
used these tables, but I remember I was able to get that information from them...

Does your dictionary building tool implement ontology walking?


-----Original Message-----
From: Dligach, Dmitriy [mailto:ddligach@luc.edu] 
Sent: Wednesday, February 15, 2017 1:50 PM
To: dev@ctakes.apache.org
Subject: Re: Phenotype-specific entities

Guergana, thank you. 

Is there anything in cTAKES now for walking the UMLS ontology (e.g. for finding hypernyms,
synonyms, etc.)?


> On Feb 15, 2017, at 12:45, Savova, Guergana <Guergana.Savova@childrens.harvard.edu>
> 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.Savova@childrens.harvard.edu
> Harvard Scholar: https://urldefense.proofpoint.com/v2/url?u=http-3A__scholar.harvard.edu_guergana-5Fk-5Fsavova_biocv&d=DwIFAw&c=qS4goWBT7poplM69zy_3xhKwEW14JZMSdioCoppxeFU&r=SeLHlpmrGNnJ9mI2WCgf_wwQk9zL4aIrVmfBoSi-j0kfEcrO4yRGmRCJNAr-rCmP&m=EMsbVKH4fuTPUXGVRWfjw4vqV3ifyKdh-3K3OLUIogI&s=oAz3p_diNUmQdKL6UIfE9Vsnj1T4H5xq6CIof1jXisU&e=

> ctakes.apache.org
> thyme.healthnlp.org
> cancer.healthnlp.org
> share.healthnlp.org
> -----Original Message-----
> From: Erin Nicole Gustafson [mailto:erin.gustafson@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

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