Time, Sean, Thank you for information. I'll try it out.
Kathy On Wed, Nov 29, 2017 at 10:10 AM, Finan, Sean < sean.fi...@childrens.harvard.edu> wrote: > Excellent answers Tim! > > > Is there a way to link all this term to x-ray without have to modify > > fast dictionary for every x-ray entries? > > Unfortunately no. The dictionary can only match (give or take) the data > that it contains. I have long had an idea on how to improve this by > trickery, but I'm not sure how well it would pan out in the end ... Plus > there is the investment of time in implementation. > Anyway, you would need to add every text that you would like to match to a > dictionary. This doesn't need to be the hsqldb dictionary. ctakes can > also read plain-text files as dictionary sources. But it requires a > certain amount of crystal ball prediction on your part as you have to > provide every permutation of a term that isn't already in the hsqldb > dictionary. > > > If you are interested in anatomic locations then I would try what Tim > suggested and at the end of your piper file add: > > load RelationSubPipe > > That should add location relations (and degree-of) to your pipeline and > would be easier than trying to rely on the dictionary to pick up every > nuance. > > Sean > > -----Original Message----- > From: Miller, Timothy [mailto:timothy.mil...@childrens.harvard.edu] > Sent: Wednesday, November 29, 2017 9:48 AM > To: dev@ctakes.apache.org > Subject: Re: exact match to CUI_TERM table question. [EXTERNAL] > [SUSPICIOUS] > > On Wed, 2017-11-29 at 09:36 -0500, Kathy Ferro wrote: > > Good Morning, > > > > 1. I have a term for x-ray that has different spelling such as x.ray, > > x.rays, xray, xrays, etc... > > I see several files in > > resources\org\apache\ctakes\assertion\semantic_classes > > folder. > > I created x-ray.txt with all the terms above and hoping it will do the > > trick. No luck. > > Is there a way to link all this term to x-ray without have to modify > > fast dictionary for every x-ray entries? > > No, these files are not for the dictionary lookup and will not add > concepts to the CAS. > > > > > 2. This might not have solution, but I'll ask anyway. Looks like the > > terms has to be exact match to terms in cut_terms table. Example > > document has "x-ray right elbow" or "elbow x-ray". In the dictionary, > > I have "x- ray of elbow" and "x-ray of the elbow". Is there a way to > > pick up both of entries in the dictionary without using black box > > (list)? The term "left" > > and > > "right" might be important in some instance. > > > > How much is found really depends on the granularity of the source > resource (UMLS/SNOMED) and whatever tricks Sean's import tool applies. > UMLS often represents relations as concepts (elbow x-ray is in there). > But as the modifiers get added it sometimes is easier to model as > relations. For example, if you can detect "left" as a modifier, "elbow" > as AnatomicalSite, and "x-ray" as procedure, then a relation extractor > should find with "left" is modifying "elbow" and x-ray modifies > "elbow," to give a complete picture. cTAKES can do relations between > anatomical sites and other arguments, but I don't know if the default > release does body side (left,right). > > > 3. This sample is kinda related to #2. Document has term "diabetes" > > in one > > sentence. Down several pages, it has more specific term such as " > > retinopathy" and "controlled with insulin". > > What is the best way to handle this? Do you suggest I add > > "'retinopathy". > > Does cTakes has term dependency? > > > > It picks up. (E08-E13) is wide range of codes. > > PREFTERM VALUES(11849,'Diabetes Mellitus'). > > ICD10CM VALUES(11849,'E08-E13'). > > PREFTERM VALUES(11860,'Diabetes Mellitus, Non-Insulin-Dependent') > > ICD10CM VALUES(11849,'E11'). > > > > I should also have pick up these, but didn't because of the exact > > match. > > INSERT INTO CUI_TERMS VALUES(11884,0,3,'retinopathy ; > > diabetic','retinopathy') > > INSERT INTO CUI_TERMS VALUES(11884,3,6,'retina abnormal - diabet - > > relat','diabet') > > INSERT INTO CUI_TERMS VALUES(11884,1,2,'diabetic > > retinopathy','retinopathy') > > INSERT INTO CUI_TERMS VALUES(11884,0,2,'retinopathy > > diabetic','retinopathy') > > > > > > Snip of Sample text: > > chief complaint: Patient came in complaining of having chest pain. > > Procedure: chest xrays. > > Problems: > > Type 2 diabetes > > depression > > retinopathy > > patient controlled with insulin. > > > > It should definitely get "retinopathy" since that's in snomed. The > first thing I check when dictionary misses something is whether the > linguistic annotations around it are correct (sentence, token, part of > speech). > > > Sincerely appreciated you help. > > Kathy >
