knowledge acquisition in the fuzzy knowledge representation framework of a medical consultation...

13
Knowledge Acquisition in the Fuzzy Knowledge Representation Framework of a Medical Consultation System By: Karl Boegl, Klaus-Peter Adlassnig, Yoichi Hayashi, Thomas Rothenfluh, and Harald Leitich

Upload: jewel-long

Post on 24-Dec-2015

216 views

Category:

Documents


2 download

TRANSCRIPT

Page 1: Knowledge Acquisition in the Fuzzy Knowledge Representation Framework of a Medical Consultation System By: Karl Boegl, Klaus-Peter Adlassnig, Yoichi Hayashi,

Knowledge Acquisition in the Fuzzy Knowledge

Representation Framework of a Medical Consultation System

By: Karl Boegl, Klaus-Peter Adlassnig, Yoichi Hayashi, Thomas Rothenfluh, and Harald Leitich

Page 2: Knowledge Acquisition in the Fuzzy Knowledge Representation Framework of a Medical Consultation System By: Karl Boegl, Klaus-Peter Adlassnig, Yoichi Hayashi,

MedFrame/CADIAG-IV

- The predecessor: CADIAG-II - Consultation System- New Implementation- Generalized Domain Model- Fuzzy Dice

Page 3: Knowledge Acquisition in the Fuzzy Knowledge Representation Framework of a Medical Consultation System By: Karl Boegl, Klaus-Peter Adlassnig, Yoichi Hayashi,

Definitions

Fuzzy Set Theory Fuzzy Logic Fuzzy Control

Page 4: Knowledge Acquisition in the Fuzzy Knowledge Representation Framework of a Medical Consultation System By: Karl Boegl, Klaus-Peter Adlassnig, Yoichi Hayashi,

Rule-Based Fuzzy Logic System

• Rules

• antecedent

• consequent

• Fuzzifier

• inference engine

• output processor

Page 5: Knowledge Acquisition in the Fuzzy Knowledge Representation Framework of a Medical Consultation System By: Karl Boegl, Klaus-Peter Adlassnig, Yoichi Hayashi,

Fuzzy Logic Example

tall(x) = { 0, if height(x) < 5 ft.,(height(x)-5ft.)/2ft., if 5 ft. <= height (x) <= 7 ft.,

1, if height(x) > 7 ft. }

Membership Function

1.0 + +-------------------

| /

| /

0.5 + /

| /

| /

0.0 +-------------+-----+-------------------

| |

5.0 7.0

height, ft. ->

Person Height degree of tallness

--------------------------------------

Billy 3' 2" 0.00

Yoke 5' 5" 0.21

Drew 5' 9" 0.38

Erik 5' 10" 0.42

Mark 6' 1" 0.54

Kareem 7' 2" 1.00

Page 6: Knowledge Acquisition in the Fuzzy Knowledge Representation Framework of a Medical Consultation System By: Karl Boegl, Klaus-Peter Adlassnig, Yoichi Hayashi,

Logic Operations in Fuzzy Logic

truth (not x) = 1.0 - truth (x)

truth (x and y) = minimum (truth(x), truth(y))

truth (x or y) = maximum (truth(x), truth(y))

Page 7: Knowledge Acquisition in the Fuzzy Knowledge Representation Framework of a Medical Consultation System By: Karl Boegl, Klaus-Peter Adlassnig, Yoichi Hayashi,

Another Example

old (x) = { 0, if age(x) < 18 yr.

(age(x)-18 yr.)/42 yr., if 18 yr. <= age(x) <= 60 yr. 1, if age(x) > 60 yr. }

a = X is TALL and X is OLD

b = X is TALL or X is OLD

c = not (X is TALL)

height age X is TALL X is OLD a b c

------------------------------------------------------------------------

3' 2" 65 0.00 1.00 0.00 1.00 1.00

5' 5" 30 0.21 0.29 0.21 0.29 0.79

5' 9" 27 0.38 0.21 0.21 0.38 0.62

5' 10" 32 0.42 0.33 0.33 0.42 0.58

6' 1" 31 0.54 0.31 0.31 0.54 0.46

7' 2" 45 1.00 0.64 0.64 1.00 0.00

3' 4" 4 0.00 0.00 0.00 0.00 1.00

Page 8: Knowledge Acquisition in the Fuzzy Knowledge Representation Framework of a Medical Consultation System By: Karl Boegl, Klaus-Peter Adlassnig, Yoichi Hayashi,

Representation within MedFrame/CADIAG-IV

Positive Associations FP Consequent => Antecedent

SP Antecedent => Consequent

Negative Associations FN -(Consequent) => Antecedent

SN Antecedent => -(Consequent)

Page 9: Knowledge Acquisition in the Fuzzy Knowledge Representation Framework of a Medical Consultation System By: Karl Boegl, Klaus-Peter Adlassnig, Yoichi Hayashi,

Knowledge Refinements (1 of 2)

Page 10: Knowledge Acquisition in the Fuzzy Knowledge Representation Framework of a Medical Consultation System By: Karl Boegl, Klaus-Peter Adlassnig, Yoichi Hayashi,

Knowledge Refinements (2 of 2)

Page 11: Knowledge Acquisition in the Fuzzy Knowledge Representation Framework of a Medical Consultation System By: Karl Boegl, Klaus-Peter Adlassnig, Yoichi Hayashi,

Project Successes

Page 12: Knowledge Acquisition in the Fuzzy Knowledge Representation Framework of a Medical Consultation System By: Karl Boegl, Klaus-Peter Adlassnig, Yoichi Hayashi,

References Title: Knowledge Acquisition in the Fuzzy Knowledge Representation Framework

of a Medical Consultation System By: Karl Boegl, Klaus-Peter Adlassnig, Yoichi Hayashi, Thomas Rothenfluh, Harald Leitich Copyright: 2001

Title: The MedFrame Project http://medexpert.imc.akh-wien.ac.at/MedFrame/

By: Dieter KopeckyCopyright: 2000

Title: Medical Expert Systems http://www.computer.privateweb.at/judith/name_3.htm

By: Judith FederhoferCopyright: 2002

(More)

Page 13: Knowledge Acquisition in the Fuzzy Knowledge Representation Framework of a Medical Consultation System By: Karl Boegl, Klaus-Peter Adlassnig, Yoichi Hayashi,

References (continued)

Title: Systematized Nomenclature of Medicine

http://www.snomed.org

By: College of American Pathologists

Copyright: 2001-2003

http://www-2.cs.cmu.edu/Groups/AI/html/faqs/ai/fuzzy/part1/faq/html Mendel, Jerry. “Uncertainty in Fuzzy Logic Systems.” University of

Southern California.