NATURAL LANGUAGE INPUT TO A COMPUTER-BASED 
GLAUCOMA CONSULTATION SYST~ 
Victor B. Cieslelski, Department of Computer Science, 
Rutgers University. New Brunswick, N. J. 
Abstract: A "Front End" for a Computer-Based Glaucoma 
Consultation System is described. The system views a 
case as a description of a particular instance of a class 
of concepts called "structured objects" and builds up a 
representation of the instance from the sentences in the 
case. The information required by the consultation 
system is then extracted and passed on to the 
consultation system in the appropriately coded form. A 
core of syntactlc, semantic end contextual rules which 
are applicable to all structured objects is being 
developed together with a representation of the 
structured object GLAUCOMA-PATIENT. There is also a 
facility for adding domain dependent syntax, 
abbreviations and defaults. 
system that has a core of syntax and semantics that is 
applicable to all structured objects and which can be 
extended by domain specific syntax, idioms and defaults. 
Considerable work on the interpretation of hospital 
discharge summaries, which are very similar to case 
descriptions, has been done by a group at NYU 
\[Sager 1978\]. Their work has focused on the creation of 
formatted data bases for subsequent question answering 
and is syntax based. The research reported here is 
concerned with extracting from the case the information 
understandable by a consultation system and is primarily 
knowledge based. 
I. STRUCTURED OBJECTS 
During the past decade a number of Medical Consultation 
systems have been developed, for example INTERNIST 
\[Pople. Myers and Miller 1973\], CASNET/GLAUCOMA 
\[Weiss st. al. 1978\], MYCIN \[Shortliffe 1976\]. Currently 
still others are being developed. Some of these programs 
are reaching a stage where they are being used in 
hospitals and clinics. Such use brings with it the need 
for fast and natural communication with these programs 
for the reporting of the "clinical state" of the patient. 
This includes laboratory findings, symptoms, medications 
and certain history data. Ideally the reporting would be 
done by speech but this is currently beyond the state of 
the art in speech understanding. A more reasonable goal 
is to try to capture the physicians" written "Natural 
Language" for describing patients and to write programs 
to convert these descriptions to the appropriate coded 
input to the consultation systems. 
The original motivation for this research came from the 
desire to have natural language input of cases to 
CASNET/GLAUCOMA a computer-based glaucoma consultation 
system developed at Retgers University. A case is 
several paragraphs of sentences , written by a physician, 
which describe a patient who has glaucoma or who is 
suspected of having glaucoma. It was desired to have a 
"Natural Language Front-End" which could interpret the 
cases and pass the content to the consultation system. 
In the beginning stages it was by no means clear that it 
would even be possible to have a "front end" since it was 
expected that some sophisticated knowledge of Glaucoma 
would be necessary and that feedback from the 
consultation system would be required in understanding 
the input sentences. However during the course of the 
investigation it became clear that certain 
generalizations could be made from the domain of 
Glaucoma. The key discovery was that under some 
reasonable assumptions the physic iane notes could be 
viewed as descriptions of instances of a class of 
concepts called structured oblects and the knowledge 
needed to interpret the notes was mostly knowledge of the 
relationship between language and structured objects 
rather than knowledge of Glaucoma. 
This observation changed the focus of the research 
somm~at - to the investigation of the relationship 
between language and structured objects with particular 
emphasis on the structured object GLAUCOMA-PATIENTo This 
change of focus has resulted in the development of a 
A structured object is like a template \[Sridharan 1978\] 
or unit \[gobrow and Winograd 1977\] or concept 
\[Brachman 1978\] in that it implicitly defines a set of 
instances. It is characterized by a biererchial 
structure. This structure consists of other structured 
objects which are components (not sub-concepts\[). For 
example the structured obJect PATIENT-LEFT-EYE is a 
component of the structured object PATIENT. Structured 
objects also have attributes, for exemple PATIENT-SEX is 
an attribute of PATIENT. Attributes can have numeric or 
non-nemeric vAlues. Each attribute has an associated 
"measurement concept" which defines the set of legal 
values, units etc. 
A structured object is represented as a. directed graph 
~here nodes represent components and attributes, and arcs 
represent relations between the concept* and its 
components. The graph has a distinguished node, 
analogous to the root of a tree, whose label is the name 
of the concept. All incoming errs to the concept enter 
only at this distinguished or "head" node. Figure I is a 
diagram of part of the structured object GLAUCOMA- 
PATIENT. There are only a limited number of relations° 
These are: 
ATTR This denotes an attribute llnk. 
MBY Associates an attribute with its measurement. 
PART The PART relation holds between two concepts. 
CONT The CONTAINS relation holds between two concepts. 
ASS An ASSOCIATION llnk. Some relations, such as the 
relation between PATIENT and PATIENT-MEDICATION 
cannot be characterized aa ATTR, PART or CONT but 
are more complex, as shown by the followln$ 
examples: 
the age of the patient (ATTR) (I) 
The medication of the patient (ASS) (2) 
The patient is receiving medication (ASS) (3) 
The patient is receiving age (?) (4) 
Although the relation between PATIENT and PATIENT- 
MEDICATION has some surface forms that make it look 
like an ATTR relation this is not really the case. 
A "true" structured object would not have ASS links 
but they must be introduced to deal with GLAUCOMA- 
PATIENT. the formal semantics of the ASS relation 
are very similar to those of the ATTR and PART 
relations. 
This research was supported under Grant No. RR-643 from 
the National Institutes of Health to the Laboratory for 
Computer Science Research. Rutgers University. 
* A~thouah the class of structured objects is a subset of 
the class of concepts the t~o teems will be used 
lnterchangeably. 
103 
//~-~AT-~'~ }~,,FO~A~ 
PART SI~C 
C I-PAT-LE 
  C2-PAT-EYE j 
q S~E ! 
C I-PAT-LE 
PRESSURE 
M. ~c~-PAT-~YE \[ 
C I-PAT-LE , 
PRESSURE-MSMT 
nESSURE-"S~'T, I 
SUBC 
C l-PAT-RE J ATI"R C I-PAT-P.E 
PRESSURE 
C I-PAT-~E- 
PRESS~E-MSMT 
~C~-~AT- I PART 
....~S- J MEDICATION j 
C I-PATIENT 
ATTR 
C I-PAT-NED- 
DL~MOX 
i c x-~ATIENT- i MET .~ c X-~AT~NT- i 
ATT~ 
c,-,ATI,.NT- ,Ic -pAT ' NT: i SEX JH (@1 SEX.-~T l 
/i -T d Ol-,A'- zo- f oz,~ox-~zQ 1 ~ ,\]OL~OX.-Z'RZq-HSM~. 
ATrP,. / 
ATTR ~ C I-PAT'HED- I MBTJ C I-PAT-MED- J 
i I DZsXoE,-OosEI '1 Dz~ox Dosz..~SHT I 
Part of the Struc~Ject GLAUCCMA~PATZENT 
FOCATTE (Focussln$ ALtribute) If there are aultlpla 
idm~tical sub-parts then typically (but not al~ys) 
the values of a particular attribute are used to 
distinKuish between them, 
SUBC One concept is a sub-concept of another. 
~e PART, COHT and ASS links are qualified by N~ME\]m and 
MODALITY as in \[Braclman 1978\]. MODALITT can have too 
values NECESSARY and OPTIONAL. Modality is used to 
reprexnt the fact ~rat eyes are necessary parts of 
patients bu~ scotouaa (bllnd-spots) may or may not be 
present in the visual field. WOMBEK can be either a 
umber (e.s. 2 EYES) or a predl~ata (e.S. >-0 ecotonae). 
The tarKeC of • PART CONT or ASS relation can also be a 
flat as in 
C I -PATIENT -LEFT-EYE-V~S UAL-F IELD 
C~T (AS'tOY 
C I-PATIENT-LEYT-g YE-VTS UAL-F IELD-SC OT~IA, 
C I-PATIENT-LEFT-EYE-V~S UAL-F IELD-ISLAND, 
the first member of the tint is e "sele~tlon function" 
~hich describes hoe elmeats are to be Marred free the 
tint • 
The nunbers after the C prefix in Fisure l donate levels 
of "sub-conceptln8". Level I £s the lowest level, those 
concepts do not have any sub-concepts only £natancao. 
Note that CI-PATIENT-KIGHT-EYE is a sub-concept of C2- 
PATIENT-gYE, not an Instanceo CI-PATIENT-LEFT-gYE and 
C2-PATTENT-~IGHT-EYE are two different concepts t that is 
they have d/~Joint sub-structure; they are as different 
to the system as C-AiM and C-LEG. There is 8nod reason 
for this. It is possible that a different Instrument 
will be needed to measure the value of an attribute in 
the right eye than in the taft aye. Thls means that the 
measurement concepts got these attrlbutee will have to he 
different for the left and right eyes. Another example 
from the d~ain of slancoma show this more vividly. CI- 
PATIENT-LEYT-~YE-VISUAL-FIELD-~COTCMA denotes a scotoma 
in the left eye. A particular type of scotoma is the 
arcuate (bow-shaped) scotoma. This must be a separate 
concept since it is meaninsful to suty "double arcuste 
scotoma" but not "doubte scotoma", This means that the 
concept C .... -FIELD-AACUATE-SCOTflMA has an attribute ~hat 
cannot be inherited from C..,-~IELD-SCOTOMA. If a 
measurement concept is the alune for hor~ eyes (or any 
other Idsetlcal sub-parts) then it need only be defined 
once and SUBC pointers can be used to point to the 
definition. An example of this is the pressure 
tuscan=ameer in likuta l. 
104 
There are many more levels of "sub-conceptlng" chat could 
be represented here but it is not necessary for the 
interpretation of the cases. Only those mechanisms for 
manipulating structured objects that are necessary for 
the interpretation of cases are beln E implemented. 
Brachmen \[Brachman 1978\] has examined the problems of 
representing concepts in considerably more detail. 
I. 1 MEASL~EMENT CONCEPTS 
Measurements are associated with those nodes of the graph 
Chat have Ineomln8 ATTR ~rcs. There are twn kinds of 
measurements those with numerical values and those with 
non-n~erlcnl values. Numerical measurements have the 
followln E internal structure: 
RANGE A pair of numbers that speclfy the range. 
UNITS A set of units for the measurement. 
QVALSET A set of qualitative values for the measurement. 
TIME A dace or one of the values PAST, PRESENT. 
INSTR A set of possible instruments for taking the 
maeaur amen, • 
CF A confidence factor or measure of reliability for 
the measurement. 
There is also soma procedural knnwledge assoclatad with 
measurm-ents. This relates numerical values to 
quantitative values, fellah Ill,lea with instruments etc. 
An example of a measurement concept is given in figure 2. 
m | i 
C I -FATIENT-LEFT-K YE-FLUI D-FR ES S UR E-M SMT 
RANGE 0, 120 
UNITS K-~4-HG 
QVALSET (ONEOF K-DECREASED, K-NORMAL, 
K-ELEVATED, K-SEVERELY-ELEVATED) 
TIME (ONEOF PAST, PRESENT, DATE) 
INSTR (ONEOF K-A PPLANAT TON -T ONOM ETER, 
K-SCHIOTZ -TONOM ETER ) 
CF O, I *************************** 
if VALUE < 5 then **ERROR** 
if 5 <- VALUE < i0 than QVAL - K-DECREASED 
if l0 <- VALUE < 21 than QVAL - K-NORMAL 
if 21 <- VALUE < 30 then QVAL - K-ELEVATED 
if 30 <- VALUE < I00 then QVAL - K-SEVERELY-ELEVATED 
if I00 <- VALUE than **ERROR** 
Fi~ur e 2 
The Measurement Concept for Intra-ocular Pressure 
Items prefixed with a ~ "K 't in figure 2 denote constants. 
Constants are "terminal items" having no further 
definition in the representation of the structured 
object. 
number of instances is known beforehand, for example 
there can only be one instance of CI-PATIENT~.EFT-EYE0 
while in other cases the number of instances is 
determined by the input, for example measurements of 
In,re-ocular pressure at different times are different 
instances. Instances are created along a number of 
dimensions, the most common one being TIME, for example 
pressure today, pressure on Mar 23. When different 
instruments are used to take measurements this 
constitutes a second dimension for instances. The rules 
of instantlatlon are embedded in the core. 
A partial instantiation of CI-PATIENT can be done before 
the first sentence is processed by tracing links marked 
NECESSARY. Any component or attribute ins,an,laced at 
this stage will be introduced by a definite noun phrase 
while optional components will be introduced by 
indefinite noun phrases. 
2. SEMANTICS 
A fundamental assumption that has been made and one that 
is Justlfled by examination of several sets of cases is 
that the sentences dascrlbe an instance of a patient with 
the assumption that the reader already knows the concept. 
None of the sentences in the notes examined had an 
interpretation which would requlre updating the concept 
GLAUCCMA-PATIENT. The interpretation of a case is thus 
consldared to be the construction of the the 
corresponding instance of GLAUCOMA-PATIENT. 
The nature of structured objects as outlined above 
dlccataa that only two fundamental kinds of assertions 
are expected in sentences. There wlll either be an 
assertion about the existence of an optional component as 
in (5) or about the value of an attribute as in (6) and 
(7) • 
There Is an arcuete scotoma od.** 
The pressure is 20 in the left eye. 
The pressure is normal os. 
(5) 
(6) 
(7) 
Vary few of the sentences contain Just one assertion, 
most contain several as in (8) and (9). 
There is a nasal step and an arcuete 
scotoma in the left eye and a central 
island in the right eye (8) 
~he medication is I0 percent pilocarplne 
daily in both eyes. (9) 
2. I THE MEANING OF A SENTENCE 
Even though sentences are viewed as containing assertions 
their meanings can be represented as sets of instances, 
Non-nmnerlcal measurements differ from numerical given that there is a procedure which takes these 
measurements in that RANGE, UNIT and QVALSET are replaced instances and incorporates them into the growing instance 
by VALSET. One or more members of VALSET are to be of GLAUCOMA-PATIENT. Ibis is due to the tree structure 
selected in creating an instance of the measurement of instances since Instantlatlon of a concept involves 
concept, for example: Instantlatlon of all concepts between itself and the 
root. In fact, many sentences in the cases do not even 
CI-PATIENT-SEX-MSMT VALSET (ONEOF K-MALE K-FEMALE) contain a relation but merely assert the existence of an 
instance or of an attribute value as in (I0) and (\[1). 
I. 2 INSTANCES 
An instance of a structured object is represented as a 
tree. Instances are created piece-meal as the 
Information trickles in from the case. In some cases the 
Nasal step od. (I0) 
a I0 year old white male. (II) 
** Opthalmologlsts frequently use the abbreviations "ed" 
for "in the right eye", "os" for "in the left eye" and 
"ou" for "in hor/1 ayes" 
105 
2.2 PROVISIONAL INSTANCES 
Any particular noun or adjective could refer to a number 
of different concepts. "Medication" for" example could 
refer to CI-PATIENT-MEDICATION, CI-PATIENT-&IGHT-EYE- 
MEDICATION or (I-PATIENT-LEFT-EYE-MEDICATION. Moreover 
in any particular use it could be referring Co one or 
more of its possible referents. In (t2) 
Medicacion consists of diamox 
and pllocarpine drops in both eyes. (12) 
"medication" refers co all of its possible referents 
since diamox is not given to the eye but is taken orally. 
In addition to this, ic £s generally not possible to know 
at the clme of encountering a word whether it refers to 
an existing Instance or to a new instance. This is due 
to the fact thaC at the time of encountering a reference 
to a concept all of the values of the instance dimensions 
mlghc not be known. The mechanism for dealing with these 
problems is Co assign "provisional Instances" as the 
referents of words end phrases when they are scanned 
during the parse and to turn these provisional instances 
Into "real" instances when the correct parse has been 
found. This involves finding the values of the instance 
dimensions from rest of the sentence, from knowledge of 
defaults or perhaps from values in previous sentences. 
The most common Instance dimension is TIME and its value 
is readily obtained from the tense of the verb or from a 
clme phrase. If the instance dimensions indicate an 
existing instance then the partial provisional instance 
from the sentence is incorporated into the existing real 
instance, otherwise a new instance is created. 
2.3 FINDING THE MEANING OF A SENTENCE 
Several mappings can be made from the representation of 
structured objects to syntactic classes. For example, 
all nodes will be referred to by nouns and noun phrases, 
links will be referred to by prepositions and verbs and 
members of a VALSET or a 0VALSET will ba referred to by 
adjectives. The links between concepts and cha ~rds 
that can be used to refer to them are made at system 
build time when che structured object is constructed. 
Some words such as "both" and "very" refer to procedures 
whose actions are the same no matter what the structured 
object. 
The nature of structured objects and of the sentences in 
cases Indicate thac a "case'* \[Bruce 1975\] approach to 
semantic analysis is a "natural". A case syecsm ham in 
fact been implemented with such cases as ATTRIBUTE, 
OBJECT, VALUE, and UNIT. One case that is particularly 
useful is FOCUS. It is used to record references Co left 
eye or right eye for use in embedded or conjoined 
sentences such as (13). 
The pressure in the left eye is 27 
and there is an arcuate scocoma. (13) 
For the reasons discussed in section 2.2 ic is necessary 
co assign sacs of candidate referents to soma of the case 
values during the course of the parse. These sacs are 
pruned as higher levels of the parse tree are built. 
3. SYNTAX 
It is noc really possible to vlew cha sentences 
comprising a case as a subset of English since many of 
the elementary grammatical rules are broken (e.g. 
frequent omission of verbs). Rather the sentences are in 
a medical dialect and parr of the task of wrlClng an 
interpreter for cases involves an anthropological 
investlgaclon of the dialect and its definition in some 
formal way. An analysls of a nt~"ber of cases revealed 
the following characteristics (see also \[Sangscer 1978\]): 
I) Frequent omission of verbs and punctuation. 
2) ~ch use of abbreviations local to the 
domain. 
3) Two kinds of ellipsis are evident. In one 
kind the constituents left ouC are co be recovered 
from knowledge of the structured object; the ocher 
kind is the standard kind of textual ellipsis where 
the missing macerisl is recovered from previous 
sentences. 
4) Two different uses of adjectival and 
prepositional qualifiers can be distinguished. 
There is a referenclal use as in "in Left eye" in 
(14) and also an attributive use as in "of elevated 
pressure" in (14) 
There is a history of elevated 
pressure in the left eye. (14) 
An adjective can only have a referential use if iC 
has previously been used attrlbucively or if it 
refers to a focussing attribute. 
5) Sentences containing several assertions 
tend to tak~a one of two forms. In one of these cha 
focus is on an eye and several measurements are 
given for that eye as in (15). 
In the left eye chars is a pressure 
of 27, .5 cupping and an ercuaCe 
ecotome. (:5) 
In the other form the focus is on an attribute and 
values for both eyes are given as in (16). 
the pressure is I0 od and 20 os. (16) 
A good deal of extra syntactic complexity is 
introduced by the fact chat there are 2 eyes (a 
particular ex-,.pla of the general phenomenon of 
multiple idanclcal sub-parts). The problm- is chac 
(ha qualifying phrases "in the left / rlghc/boch 
eyes" appear in many different places in the 
sentences and conslderabla work must be done to 
find the correct scope. 
4. TMPLEM~TATTON AND AN EXAMPLE 
The system is being implemented in FUSPED a combination 
of Cha AI language FUZZY \[Lefaivre 1976\], the PEDAGLOT 
parsing system \[Fabens 1976\] and RUTLISP (&urgers 
UCILISP). I~ZZ¥ provides an associative network facility 
~ich is used for scoring both definitions of structured 
objects and instances. FUZZY also provides pattern 
marching and pattern directed procedure invocation 
facilities which are very useful for 4mplemancing 
defaults and ocher inferences. PEDACLOT is both a 
context free parser and a system for creating and editing 
grammar s • PEDACLOT "Cage" correspond Co gnuch 
syscheetzad attributes \[gnuCh t968\] and parses can be 
failed by resting conditions on rag values thus providing 
a natural imy of intermixing semantics and Farsing. 
~he ~plmmcation of the systma is noC yac complete buc 
lC can deal with a fairly wide range of sentences about a 
number of components and attributes of Cl-GLAOCCMA- 
PATIENT. Figure 3 is some edited output from a rim of 
the e3mcmm. The interpretation of only one sentence is 
i06 
shown. Space considerations prohibit the 
more of the intermediate output. 
inclusion of 
,the patient is a 60 year old white male 
*diamc~ 250 ms bid 
Meaning : 
(I 626 PATIENT MEDICATION DIAMOX DOSE MSMT) 
NVAL 250 
UNIT (K MG) 
TIME PRESENT 
INST PRESENT 
(T 630 PATIENT MEDICATION DIAMOX PREQUENCY MSMT) 
VAL (K BID) 
TIME PRESENT 
INST PRESENT 
~eplnephrlne 2 percent bid od and pilocsrpine 2 percent 
bid os 
tthe pressures are 34 od and 40 os 
tche cupping ratio is .5 in both eyes 
~in the right eye there is 20 / 50 vision and 
a central island 
tin the left eye the visual acuity is finger count 
***GLAUCOMA CONSULTATION PROGRAM*** 
CAUSAL-ASSOC IATIONAL NETWORK 
*RESEARCH USE ONLY* 
******************** 
* GLAUCOMA StHMARY * ******************** 
.)ERSONAL DATA: 
bt~4E: ANON ~gIOUS 
AGE: 60 RACE: W SEX: M 
CASE NO: 50 (HYPOTHETICAL) 
CLINICAL DATA StHMARY FOR VISIT OF 3/27/79 
CURRENT MEDICATIONS: 
PILOCARPINE 2Z BID (OS) 
EPINEPHRINE 2% BID (OD) 
DIAMOX/INHIBITOR8 250 MG BID 
BEST CORRECTED VISUAL ACUITY: 
OD: 20/20 OS: FC 
lOP: 
OD: 34 OS: 40 
VERTICAL CUP/DISC RATIO: 0.50 (OU) 
VISUAL FIELDS: 
CENTRAL ISLAND (OD) 
****,eee***e.e****e 
1. 
2. 
3. 
4. 
5. 
Pigure 3 
Some (edited) output from a run of a case 
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I07 
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