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Graphs of Consistent Concepts. Data mining in a medical domain (Pawel Matykiewicz, Wlodzislaw Duch, John Pestian). The story(1). Hospital workflow: Chest X-Ray order ( Electronical Medical Record ) Chest X-Ray ( High Quality JPEG ) - PowerPoint PPT Presentation
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Graphs of Consistent Concepts
Data mining in a medical domain(Pawel Matykiewicz, Wlodzislaw
Duch, John Pestian)
The story(1)• Hospital workflow:
– Chest X-Ray order (Electronical Medical Record)– Chest X-Ray (High Quality JPEG)– Dictation ( “CLINICAL HISTORY: 9-month-29-day-old male with a history of cough.
Rule out pneumonia.PROCEDURE COMMENTS: None.COMPARISON: XX/XX/XX.FINDINGS: There is mild hyperinflation of the lungs with increased peribronchial
markings most consistent with viral versus reactive airway disease. Hazy increased density is seen in the right middle lobe, left lower lobe which could represent subsegmental atelectasis. Hazy increased density is also noted at the lingula with partial effacement of the left heart contour which could represent atelectasis versus early pneumonia. No pleural effusion is noted. The cardiothymic silhouette is within normal limits. Soft tissues and bony structures are unchanged.
IMPRESSION: Findings most consistent with viral versus reactive airway disease. Patchy atelectasis is associated. Lingular early infiltrate cannot be excluded.” )
– Billing ( ICD9CM 590.8 = INFECTIONS OF KIDNEY: OTHER PYELONEPHRITIS OR PYONEPHROSIS, NOT SPECIFIED AS ACUTE OR CHRONIC )
Creating a novel tool(2)
Semantic memory
Recognition memory
Episodic memory
Full text annotation
UMLS (3)• UMLS = Unified Medical Language System• UMLS contains:
– 1,195,781 unique English concepts (CUI)– 2,873,310 unique English phrases (SUI) – 3,283,983 unique English, normalized words
(WUI)– 88 different ontologies (e.g. ICD9CM = 15871
CUIS)– 36,627,948 relations– 11,495,405 co-occurrence relations
Example(4)• Concept description:
– ENG|zygopleurage zygospora|C1473040|L5302079|S6018172|
– C1533582|ENG|P|L5432111|PF|S6215413|Y|A7881881|2532798015|412807000||SNOMEDCT|PT|412807000|Serum inhibin measurement|4|N||
• Relation description:– C0000039|A6841046|CODE|RO|C0364349|A0683492|CODE|has_component|R39728053||LNC|LNC||Y|N||
WUI WUI
WUI
SUI
SUI SUI
SUI
CUI
CUI CUI
CUI
CUI
Sense Disambiguation(5)• Word Sense Disambiguation:
– “cold” (word):• "I am taking aspirin for my cold" • "Let's go inside, I'm cold“
• Phrase Sense Disambiguation:– “cold” (WUI):
• cold temperature (CUI)• Common Cold (CUI)• Cold Therapy (CUI)• Chronic Obstructive Airway Disease (CUI)• Cold Sensation (CUI)• Cold brand of chlorpheniramine-phenylpropanolamine
(CUI)
Concept Mapping(6)• Tough way:
• Easy way:
Graphs of consistent concepts(7)
X versus Y Z => ( C(YZ) => C(XZ) )
X is associated => ( C(X) => P(X) = 1 )
JJ(X) => ( NN(Y) => C(XY) )
Graphs of consistent concepts(8)
Graphs of consistent concepts(9)
Summary(10)• Data set:
– 30 training documents ( 6 ICD9CM codes, 137 CUIs )– 30 testing documents ( 6 ICD9CM codes, 301 CUIs )
– 30 training documents ( 6 ICD9CM codes, 301 CUIs )– 30 testing documents ( 6 ICD9CM codes, 137 CUIs )
• To do:– Construction finding– Concept discovery– State discovery
before learning
after learning
training 66% 99%
testing 53% 66%
before learning
after learning
testing 53% 80%
training 66% 85%