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From "Finan, Sean" <Sean.Fi...@childrens.harvard.edu>
Subject RE: Section finder performance characteristics
Date Thu, 23 Feb 2017 17:35:22 GMT
Hi Andrey,

I gave up on the CDA Sectionizer and created the RegexSectionizer in core.  It is incredibly
simple - it just takes in a list of regexes that fit section headers  - and footers if they
exist.  If you can create a regex that fits most situations, like a blank line and some short
all-caps string, then you are all set.  I don't think that I checked in unit tests as for
my project I am using regressions.

Have a look if you like.

Sean

-----Original Message-----
From: Andrey Kurdumov [mailto:kant2002@googlemail.com] 
Sent: Wednesday, February 22, 2017 12:40 PM
To: cTakes developers list
Subject: Re: Section finder performance characteristics

Thanks Chen for your response,

I read source code of CDA sectionizer and came to same conclusion that it is highly specific
to the data on which it would be working.

Unfortunately on my project, I would not know how data would looks like, until I start working
with it. I expect that data would be very diverse, so handcrafting cda_section.txt for each
dataset would be too expensive for me.
I would like to have some sort of sectionizer which recognize 95%-99% of sections, without
mapping to LOINC/HL7 initially. I need such precision since I will use section name down the
pipeline to narrow search of conditions in the each section. For example if I found section
'Family history', I could narrow search of SNOMED concepts only related to family history
and throw others.

What I try to find out, what performance existing CDA sectionizer in numbers?
Does anybody able to create custom cda_section.txt file which works well across diverse set
of clinical notes?
What size of datasets CDA sectionzer was tested on?
I expect that current implementation would not meet my goals on wide range of clinical notes
from different domains since at some point it very likely start producing regressions. But
I would like that somebody prove that my assumptions are wrong.

Also I interested what are the process to improve CDA sectionizer? Right now there no test
cases for it, dataset on which it was tested unknown to me, and if I made some change which
work for me, likely it break something for somebody which is bad. Does anybody has and idea
how this could be handled?

Best regards,
Andrey



2017-02-22 22:25 GMT+06:00 Lin, Chen <Chen.Lin@childrens.harvard.edu>:

> Hi Andrey,
>
> The CDA sectionizer is a rule/RegEx based method for section header 
> matching. It follows the consolidated CDA/HL7 standard for defining a 
> section header template. The template format is:
> HL7 template id, LOINC Section Code, and a list of n header names 
> (case insensitive, n can be as many as possible)
>
> For example, a history related section-header template can be defined as:
> history,1,brief history of physical illness,history of present 
> illness,history of the present illness
>
> ³history² is the entry id (named by yourself), ³1² is the Section code 
> (named by yourself), The rest are the permutation of history-section 
> headers that appear in a dataset. Note it is very specific, if you 
> only list ³history of present illness², it will not find ³history of 
> [the] present illness² unless you list both.
>
> As you can see it¹s a strict template matching algorithm, so if you 
> know your data, especially all the section headers, it can surely do 
> the job. I have used CDA sectionizer for two projects. Those notes I 
> processed were with standard section header format so the performance was acceptable.
>
> Hope it is helpful.
>
> Best,
> Chen
>
>
>
> On 2/22/17, 3:23 AM, "Andrey Kurdumov" <kant2002@googlemail.com> wrote:
>
> >Does anybody know what expected performance of the current CDA 
> >section finder in cTakes?
> >
> >How it was created, since I don't see any test cases for it? Does it 
> >was created on public or private dataset?
> >
> >Best regards,
> >Andrey Kurdyumov
>
>
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