1. INTERNIST-I/ CADUCEUS
A medical diagnostic assistant expert system
Created By: Dr. Harry Pople,
Dr. Jack Myers, and Randolph Miller
A little about what it is:
Medical diagnosis system
Developed in the 70’s and 80’s
By Pople, Myers and Miller
Most other Medical expert systems at the time of development were focused on making patient diagnosis on a small area of medicine this program attempts to cover internal medicine
Internist-I was developed first and has a different internal data then caduceus does.

2. Goal Cover a broad area of the internal medicine domain.
Make accurate classification of the diseases that patients have
Explain what caused the disease(s)
Going to do this by reasoning like a doctor

3. Reasoning Like a Doctor
Try to model the method that doctors follow in diagnosis
Assumptions:
Doctors quickly narrow down possible disease(s)
The patient is assumed to have one disease until otherwise shown.
(reduces the search space)
Doctors quickly narrow down possible disease(s) of a patient by having expert knowledge of diseases and their interactions with the body
The patient is assumed to have one disease until otherwise shown.
(reduces the search space)

4. The System Task: Classification & Synthesis Code: InterLisp Data:
500 diseases
3500 manifestations
This covers 70-75% of internal medicine
Actually two systems INTERNIST-I and CADUCEUS (INTERNIST-II)
TASK: Classification for classifying a disease
Synthesis for formulating hypothesis from individual manifestations
The data was gathered from:
years of following consultants in the field and medical papers

5. Data Structure Pathophysiological(causal) Model –
A causal interaction of diseases, symptoms, derangements, abnormal lab values, etc…
Nosological Structure
A Taxonomy of disease (not a strict hierarchy)

6. Terms Manifestation – Findings Disease Entity – Actual Disease
Symptom, sign, abnormal lab values…
(Shock, Common duct stone, jaundice,…)
Disease Entity – Actual Disease
Gilbert’s Disease, Viral Hepatitis, …

7. Causal Model … … caused by
- Manifestation
- Disease States
Syndromes,
pathological derangements, and other entities
caused by … …
Disease entities  Findings ( symptoms, signs, abnormal lab values…)
syndromes, pathological
derangements, other stuff
particular to the disease process
Findings (Manifestations)  Disease Entities

8. Causal Model caused by B A C D E A is CAUSED BY B E is CAUSED BY D
- Manifestation
- Disease States
caused by B
B is a
Disease Entity A
A is a Symptom C
C is a
syndrome D
D is a
Disease Entity
Findings ( symptoms, signs, abnormal lab values…)  Disease entities
syndromes, pathological
derangements, other stuff
particular to the disease process E
E is an
Abnormal
Lab Value
A is CAUSED BY B
E is CAUSED BY D
A is CAUSED BY C is CAUSED BY D
A is CAUSED BY B OR C

9. Causal Model Network of A is caused by B
Disease entities  Findings ( symptoms, signs, abnormal lab values…)
syndromes, pathological
derangements, other stuff
particular to the disease process

10. Nosological Structure
A disease can be classified into many different areas so this is not a strict hierarchy

11. INTERNIST-I Causal Model Method
Disease profile: (evoking strength, frequency)
Manifestation: (import value)
Method
Create a list of possible diseases evaluate the hypothesis to conclude a disease.
Score = Explained – Unexplained
Disease Profile
Evoking strength – “Given a patient with this findings how strongly should I consider this diagnosis to be its explanation?”
Frequency is an estimate of how often a patients with the disease have the finding.
Manifestation:
Import – disease independent
- Global importance of the manifestation (the extent to which one is compelled to explain its presence in any patient
Method of diagnosis
create a list of possible diseases
rank them-
SCORE = sum of a positive and a negative component
POSITIVE COMPONENT = the weights of all manifestations explained by the hypothesis (based on evoking strength of the observed manifestation for the diagnosis [ weighting scale 0 1pt, 1 4pts, 2 10pts, 3 20pts, 4 40pts, 5 80pts ]) Any disease related to an already concluded hypothesis gets an extra 20 pts.
NEGATIVE COMPONENT = weights of all manifestation of the disease that are not present in the patient but are expected to occur in the disease. (based on expected frequency of manifestation [ 1 –1pts, 2 –4pts, 3 –7 pts, 4 –15pts, 5 –30pts]) Also includes all the weights of all manifestation present in the patient but not explained by the hypotheses diagnosis. IMPORT (1 –2pts, 2 –6pts, 3 –10pts, 4 –20pts, 5 –40pts)
METHOD
Creates a list of possible diseases
Chooses most likely
Tries to prove or disprove it using hierarchy
If still have hypothesized diseases left
Ask user questions
PURSUE (prove 1 increase score), RULE-OUT (eliminate 5+), DISCRIMINATE (2-4 maximize spread of scores)
Conclude a result
Manifestation*Evoking
Manifestation*Frequency
Manifestation*Import

12. INTERNIST-I Example
INITIAL POSITIVE MANIFESTATIONS:
+ AGE GTR THAN 55
+ ARTHRITIS HX
+ DEPRESSION HX
+ SEX FEMALE
+ THYROIDECTOMY HX
+ ULCER PEPTIC HX
+ URINE DARK HX
+ WEIGHT INCREASE RECENT HX
+ ANOREXIA …
+ STOMACH BARIUM MEAL HIATAL HERNIA
+ DENY
INITIAL NEGATIVE FINDINGS:
-ALCOHOLISM CHRONIC HX
-DIARRHEA CHRONIC
-FECES BLACK TARRY
-FEVER
-PRESSURE VENOUS INCREASED ON INSPECTION
-ESOPHAGUS BARIUM MEAL VARICES
-STOMACH BARIUM MEAL ULCER CRATER
-T3 RESIN UPTAKE INCREASED
-T4 TOTAL BLOOD INCREASED
-GO
DISREGARDING: DEPRESSION HX, WEIGHT INCREASE RECENT HX, CHEST PAIN LATERAL EXACERBATION WITH BREATHING, CHEST PAIN LATERAL SHARP, …, GLUCOSE BLOOD 130 TO 300, AMMONIA BLOOD INCREASED, ASCITIC FLUID WBC 100 TO 500, GLUCOSE TOLERANCE DECREASED
CONSIDERING: AGE GTR THAN 55, SEX FEMALE, URINE DARK, ANOREXIA, FECES LIGHT COLORED, JAUNDICE, LIVER ENLARGED MODERATE, SKIN PALMAR ERYTHEMA, …, PROTHROMBIN TIME INCREASED, RHEUMATOID FACTOR POSITIVE.
DISCRIMINATE: HEPATITIS CHRONIC ACTIVE, BILIARY CIRRHOSIS PRIMARY   

13. INTERNIST-I Example … Please Enter Findings of LIPID(S) BLOODGO
CHOLESTEROL BLOOD DECREASED?
N/A
Please Enter Findings of INSPECTION AND PALPITATION SKIN
SKIN XANTHOMATA? NO
Please Enter Findings of BLOOD COUNT AND SMEAR
 GO
RBC TARGET(S)? …
CONCLUDE: HEPATITIS CHRONIC ACTIVE
DISREGARDING: DEPRESSION HX, CHEST PAIN LATERAL EXACERBATION WITH
BREATHING, CHEST PAIN LATERAL SHARP, … 
CONSIDERING: WEIGHT INCREASE RECENT HX, ABDOMEN DISTENTION, ASCITIC FLUID PROTEIN 3 GRAM(S) PERCENT OR LESS ...
CONCLUDE: TRANSUDATIVE ASCITES
DISREGARDING: ...
CONSIDERING: ASTERIXIS, PULSE PRESSURE INCREASED, TACHYCARDIA, AMMONIA BLOODINCREASED
PURSUING: HEPATIC ENCEPHALOPATHY
CSF FLUID OBTAINED?
CONCLUDE: HEPATIC ENCEPHALOPATHY

14. INTERNIST-I Testing No. of instances Category INTERNIST-I Clinicians
Discussants
Definitive, correct 17 23 29
Tentative, correct 8 5 6
Failed to make correct diag. 18 15
Definitive, incorrect 11
Tentative, incorrect 2
Total incorrect 13
Total no. errors in diagnosis 28 21
Total possible diagnoses 43
Summary of results for major diagnoses in 19 cases used in the INTERNIST-1 evaluation
New England Journal of Medicine --- Case Records of the Massachusetts General hospital
1969

15. Problems Knowledge-base errors Computer-program faults
Data base incomplete/omissions (2)
Data base incorrect (2)
Lack of anatomic knowledge (1)
Failure to represent degree of severity (2)
Computer-program faults
Lack of temporal reasoning (3)
Failure of scoring algorithm (3)
Failure to seek global overview (1)
Improper attribution of findings to a concluded diagnosis (6)
Limitations due to the structure or content of the knowledge base.
Examples include the absence of a manifestation required to describe an important finding
The use of overly simplistic manifestations for some circumstances
The inadvertent omission of a finding from a disease profile
The assignment of an incorrect evoking strength, frequency, or import
The failure of a manifestation to convey adequate anatomic information
Deficiencies in the design or implementation (or both)
Failure to incorporate temporal reasoning capabilities
Problems resulting from use of the scoring algorithm
Inability to take a broad overview in attacking a complex problem
Improper attribution of findings to concluded diagnoses (I.e. invoking the wrong explanation for a finding)

16. Solution: CADUCEUS New Data Structure New Method:
Combine Causal and nosologic hierarchies
New Method:
State space search with evaluation across states.
Eliminate possible areas of hierarchies

17. Data Structure

18. CADUCEUS Results CADUECUS is better then INTERNIST-I
Gets to answer faster
Less consultations to the doctor
Eliminates huge parts of the search right away
Lack of temporal reasoning

19. Conclusion Goal Met: Goal not met:
INTERNIST-I and CADUCEUS do cover a large area of internal medicine
Goal not met:
Accurately classify a patients diseases
Explain systems results to the user
Goal not met
Although the system does do this it does not do it well enough for it to be used in a real life situation

20. Questions

21. Combinations