1 negation & null values rough “chalk talk” notes alan rector 2005-05-28 (revised...

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1 Negation & Null Values Rough “chalk talk” notes Alan Rector 2005-05-28 (revised 2005-06-12)

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Page 1: 1 Negation & Null Values Rough “chalk talk” notes Alan Rector 2005-05-28 (revised 2005-06-12)

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Negation & Null Values

Rough “chalk talk” notes

Alan Rector2005-05-28

(revised 2005-06-12)

Page 2: 1 Negation & Null Values Rough “chalk talk” notes Alan Rector 2005-05-28 (revised 2005-06-12)

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Simple Version

• Case 1: Diabetes– “Some people have diabetes & some people don’t”

xy. [Person(x) & Diabetes(y) & has(x,y)]x. [Person(x) & NOT y.[ Diabetes(y) & has(x,y)]]

– “john has diabetes”• Person(john) & y[Diabetes(y) & has(john, y)]

– “john does not have diabetes”• Person(john) & NOT y[Diabetes(y) & has(john,y)]

Page 3: 1 Negation & Null Values Rough “chalk talk” notes Alan Rector 2005-05-28 (revised 2005-06-12)

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Simple Version 2:

• Temperature– “All people have a temperature that has a temperature value”

x. Person(x) yz. Temperature(y) & Temperature_value(z) & has_observable(x,y) & has_value(y,z)

– John has a temperature of 37• Person(john) & y. Temperature(y) &

Temperature_value(37_degrees) & has_observable(john, y) & has_value(y,37_degrees).

Page 4: 1 Negation & Null Values Rough “chalk talk” notes Alan Rector 2005-05-28 (revised 2005-06-12)

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Simple Negation NOT InformativeNegates too much

• Temperature– John has a temperature that is an elevated temperature

• Person(john) & yz. Temperature(y) & Temperature_value(z) & has_observable(john, y) & has_value(y,z) & elevated_for(y,z).

– John does not have a temperature that is an elevated temperature

• Person(john) & NOT yz. Temperature(y) & Temperature_value(z) & has_observable(john, y) & has_value(y,z) & elevated_for(y,z).

Page 5: 1 Negation & Null Values Rough “chalk talk” notes Alan Rector 2005-05-28 (revised 2005-06-12)

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Alternative value rather than negation

• “John has a Temperature that is not elevated”:• Person(john) & yz. Temperature(y) &

Temperature_value(z) & has_observable(john, y) & has_value(y,z) & NOT elevated_for(y,z).

Page 6: 1 Negation & Null Values Rough “chalk talk” notes Alan Rector 2005-05-28 (revised 2005-06-12)

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Information loss with negation

y . Termperature(y) & Temperature_value(z) elevated_for(y,z) OR normal_for(y,z) OR depressed_for(y,z)

– Therefore, NOT elevated does not convey (usually) all the information available

• To specify all specify the information available, give the most specific value available:“John has a temperature that is depressed”

– Person(john) & NOT yz. Temperature(y) & Temperature_value(z) & has_observable(john, y) & has_value(y,z) & depressed_for(y,z).

Page 7: 1 Negation & Null Values Rough “chalk talk” notes Alan Rector 2005-05-28 (revised 2005-06-12)

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Pedal PulsesJust a special case with two values: present/absent

• “All people can have observations of pedal pulses that can be present or absent”

x. Person(x) yz. Pedal_pulse(y) & Present_absent(z) & has_observable(x,y) & has_value(y,z)

– “John’s pedal pulse is present”• Person(john) & y. Pedal_pulse(y) &

Present_absent(present) & has_observable(john, y) & has_value(y, present).

– “John’s pedal pulse is absent”• Person(john) & y. Pedal_pulse(y) &

Present_absent(absent) & has_observable(john, y) & has_value(y, absent).

Page 8: 1 Negation & Null Values Rough “chalk talk” notes Alan Rector 2005-05-28 (revised 2005-06-12)

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Flavours of Null– “Some people with non-null observational status have

diabetes) xy. Person(x) & Diabetes(y) & non_null(x,Diabetes) & has(x,y)

– “john can be determined to have and has diabetes”• Person(john) & non_null(john, Diabetes)

& y. Diabetes(y)& has(john, y)

– “john does not have diabetes”• Person(john) & non_null(john, Diabetes)

& NOT y. Diabetes(y) & has(john, y)

– “Whether or not john has diabetes cannot be determined”• Person john & NOT non_null(john, Diabetes)

Page 9: 1 Negation & Null Values Rough “chalk talk” notes Alan Rector 2005-05-28 (revised 2005-06-12)

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Flavours of Null• Temperature

– “All people that have non-null temperature measurement have a temperature that has a temperature value” x. Person(x) & nonNull(x,Temperature)

yz. Temperature(y) & Temperature_value(z) & has_observable(x,y) & has_value(y,z)

– John has a temperature of 37• Person(john) & nonNull(x,Temperature)

y. Temperature(y) & Temperature_value(37_degrees) & has_observable(john, y) & has_value(y,37_degrees).

Page 10: 1 Negation & Null Values Rough “chalk talk” notes Alan Rector 2005-05-28 (revised 2005-06-12)

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Flavours of Null: Pedal Pulses

• “All people who’s pedal pulses might be reasonably measure can have observations of pedal pulses that can be present or absent”

x. Person(x) & nonNull(x,Pedal_pulse) yz. Pedal_pulse(y) & Present_absent(z) & has_observable(x,y) & has_value(y,z)

Page 11: 1 Negation & Null Values Rough “chalk talk” notes Alan Rector 2005-05-28 (revised 2005-06-12)

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Non-null – what does it really mean?

• Physical_possibility_status(Person, Entity) “applicability”

– Refers to the patient• E.g. Pedal pulses in a bilateral amputee

• Epistemic_status(Observer, <Person, Entity>) “validity”

– Refers to the observation, method, and sample• E.g. Could not get a clear answer; dropped specimen; haemolised; etc

• nullStatus = applicability x validity

Page 12: 1 Negation & Null Values Rough “chalk talk” notes Alan Rector 2005-05-28 (revised 2005-06-12)

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Hypothesis

• “Applicability” belongs to the clinical realm and hence to S-CT– A statement about the patient that they atypically do not

have this observable• They are an atypical patient with respect to this observable

• “Validity” belongs to the knowing realm & hence to HL7 (or other info model)– About the observation or procedure rather than the patient

• The patient may or may not be typical (we don’t know, although they probably are) but our method of knowing went wrong.

Page 13: 1 Negation & Null Values Rough “chalk talk” notes Alan Rector 2005-05-28 (revised 2005-06-12)

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IncludingValidity & applicability

• Add the notion that a statement “concerns” a finding / observable

• Add a wrapper here called “Clinical_situation” which ‘concerns’ findings/observations.

• Some basic rules– If a finding is present then the finding must be applicable to the

patient and the situation concerns the finding– A situation may concern a finding that is applicable to a patient

but absent– A finding may concern a patient but not be applicable

Page 14: 1 Negation & Null Values Rough “chalk talk” notes Alan Rector 2005-05-28 (revised 2005-06-12)

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So what is our basic form in a message or EHR

• “There is a valid observation by an observer at a time & place with respect to someone/thing of…”

– “A clinical situation that• Includes this clinical finding ( is applicable to this patient concerns this finding

)• Does not include this clinical finding but this finding is applicable to this patient

( concerns this finding)• Concerns this clinical finding and that this finding is inapplicable to this patient

– “There is a clinical situation that• Includes a observable that is applicable to this patient &

has value V ( concerns this observable)• Concerns this observable and that this observable is not applicable to this patient

• “There is an invalid observation by an observer at a time & place with respect to someone/thing of – “A clinical situation that concerns this Observable/Clinical Finding”

• The contents are not relevant since the observation is invalid

Page 15: 1 Negation & Null Values Rough “chalk talk” notes Alan Rector 2005-05-28 (revised 2005-06-12)

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More on negationWhat are we negating?

What does a code represent?

• From here on logic notation gets very unreadable– Switch to compact OWL syntax

• Roughly outline form with a few extra words– & “and” or “that”– SOME existential (the usual default link in S-CT)

• And with apologies for ignorance of some S-CT vocabulary

Page 16: 1 Negation & Null Values Rough “chalk talk” notes Alan Rector 2005-05-28 (revised 2005-06-12)

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A Rigorous formal Approach to Negation in S-CT using OWL

• Hypothesis - a code represents a “Clinical situation” (or “syndrome”)– Already present in the way S-CT is structured

• S_CT_Thing & has_morphology SOME MorphologyClass & has_site SOME AnatomicalStructure …

– Where role groups are already added • S_CT_Thing &

has_rg SOME (RoleGroup & has_morphology SOME MorphologyClass & has_site SOME AnatomicalStructure) …

Page 17: 1 Negation & Null Values Rough “chalk talk” notes Alan Rector 2005-05-28 (revised 2005-06-12)

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So if we identify tentatively for readability and intuitions

• Identify– S_CT_Thing Clinical_situation

– has_rg includes

– RoleGroup (in this context) Finding or Observable

• Then we have something like – Clinical_situation &

includes SOME (Finding has_morphology SOME MorphologyClass &

has_site SOME AnatomicalStructure)

Page 18: 1 Negation & Null Values Rough “chalk talk” notes Alan Rector 2005-05-28 (revised 2005-06-12)

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So “Skull Fracture without Haemorrage” becomes when fully expanded…

– Clinical_situatsion & includes SOME (Finding & has_morphology SOME Fracture & has_site SOME Skull) & NOT includes SOME (Finding & has_morphology SOME Haemorrhage & has_site SOME Skull)

• And the rest comes for free– At least as a reference formalism

• And for local classification– Well within the capacity of today’s classifiers locally which is all SNOMED needs

Page 19: 1 Negation & Null Values Rough “chalk talk” notes Alan Rector 2005-05-28 (revised 2005-06-12)

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DemoFrom Protege-OWl

Given a series of definitions of the form:

And underlying definitions such as

Skull_fracture_without_intracranial_haemorrhage_situation =

Intracranial_haemorrhage_finding =

Page 20: 1 Negation & Null Values Rough “chalk talk” notes Alan Rector 2005-05-28 (revised 2005-06-12)

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Then a flat list of such stated definitions for:

QuickTime™ and aTIFF (LZW) decompressor

are needed to see this picture.

Page 21: 1 Negation & Null Values Rough “chalk talk” notes Alan Rector 2005-05-28 (revised 2005-06-12)

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Will be rearranged by the OWL classifier to give the correct classification as described in handout automatically

QuickTime™ and aTIFF (LZW) decompressor

are needed to see this picture.