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
