determining the syntactic structure of medical terms in clinical notes bridget t. mcinnes ted...
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Determining the Syntactic Structure of Medical Terms in Clinical Notes
Bridget T. McInnesTed Pedersen
Serguei V. Pakhomov
Goal
The goal of this presentation is to present a simple but effective approach to identify the
syntactic structure of three word terms
Importance
Potentially improve the analysis of unrestricted medical text Mapping of medical text to standardized
terminologies
Unsupervised syntactic parsing
Syntactic Structure of Terms
w1 w2 w3 w1 w2 w3 w1 w2 w3 w1 w2 w3
Monolithic
Non-branching Right-branchingLeft-branching
blue = independencegreen = dependence
Example
small bowel obstruction
Syntactic Structure of Example
small bowel obstruction
small bowel obstruction small bowel obstruction small bowel obstruction small bowel obstruction
Monolithic
Non-branching Right-branchingLeft-branching
Method used to determine the structure of a term
The Log Likelihood Ratio is the ratio between the observed probability of a term occurring and the probability it would be expected to occur
Probability of Term Occurring-----------------------------------
Expected Probability of Term
Log Likelihood Ratio
The expected probability of a term is often based on the Non-branching (Independence) Model
P(small bowel obstruction)-----------------------------------
P(small) P(bowel) P(obstruction)
EXPECTED PROBABILITY
OBSERVED PROBABILITY
Extended Log Likelihood Ratio
The expected probabilities can be calculated using two other hypothesis (models)
Non-branching Right-branchingLeft-branching
P(small)P(bowel)P(obstruction) P(small bowel) P(obstruction) P(small) P(bowel obstruction)
Three Log Likelihood Ratio Equations
P(small bowel obstruction)-----------------------------------
P(small) P(bowel) P(obstruction)
P(small bowel obstruction)-----------------------------------
P(small bowel) P(obstruction)
P(small bowel obstruction)-----------------------------------
P(small) P(bowel obstruction)
Non-branching
Right-branching Left-branching
Expected Probability
The expected probability of a term differs as does the Log Likelihood Ratio
Non-branching Right-branchingLeft-branching
P(small) P(bowel) P(obstruction) P(small bowel) P(obstruction) P(small) P(bowel obstruction)
LL = 11,635.45 LL = 5,169.81 LL = 8,532.90
Model Fitting
The model with the lowest Log Likelihood Ratio best describes the underlying structure of the
term
Non-branching Right-branchingLeft-branching
P(small) P(bowel) P(obstruction) P(small bowel) P(obstruction) P(small) P(bowel obstruction)
LL = 11,635.45 LL = 5,169.81 LL = 8,532.90
ReCap
The Log Likelihood Ratio is calculated for each possible model Non-branching
Right-branching
Left-branching
The probabilities for each model are obtained from a corpus
The term is assigned the structure whose model has the lowest Log Likelihood Ratio
Test Set
Contains 708 three word terms from the SNOMED-CT
73 terms
Monolithic
Non-branching Right-branchingLeft-branching
6 terms 378 terms251 terms
Test Set (cont)
Syntactic structure of each term was determined through the consensus of two medical text index experts (kappa = 0.704)
The probabilities were obtained from over 10,000 Mayo Clinic clinical notes
Monolithic Results
Left branching Right branching Our Method0
10
20
30
40
50
60
70
80
Agreement
Technique
Per
cen
tag
e ag
reem
ent
wit
h h
um
an e
xper
ts
35.5
53.4
74.8
Results without Monolithic Terms
Left branching Right branching Our Method0
10
20
30
40
50
60
70
80
Agreement
Technique
Per
cen
tag
e ag
reem
ent
wit
h h
um
an e
xper
ts
39.5
59.5
83.5
Limitations
Monolithic structures possibly identify through collocation extraction or
dictionary lookup
As the number of words in a term grows so does the number of hypothesis (models) to be evaluated only consider adjacent models
limit the length of the terms to 5 or 6 words
Conclusions
Present a simple but effective method to identify the structure of three word terms
The method uses the Log Likelihood Ratio
Could be extended to identify the structure of for four, five and six word terms
Future Work
Improve accuracy of method explore other measures of association
Chi-squared, Phi, Dice coefficient ...
incorporate multiple measures together
Extend our method to four and five word terms difficulty: finding a test set
Thank you
Software:
Ngram Statistic Package (NSP)www.d.umn.edu/~tpederse/nsp.html
Log Likelihood Ratio Modelswww.cs.umn.edu/~bthomson/mti.html
Log Likelihood Equation
2 * ∑xyz ( nxyz * log(nxyz / mxyz) )
Expected Values
2 * ∑xyz ( nxyz * log(nxyz / mxyz) )
Non-branching: mxyz = nx++ * n+y+ * n++z / n+++
Left-branching: mxyz = nxy+ * n++z / n+++
Right-branching: mxyz = nx++ * n+yz / n+++