Text Mining the History of Medicine

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Mining
the
History
of
Medicine

Sophia
Ananiadou

Na-onal
Centre
for
Text
Mining

Scho...

•  Text
Mining
tools
for
enriching
content

•  Mining
the
History
of
Medicine

•  Seman-c...

raw

(unstructured)

text

part-‐of-‐speech

tagging

named
en-ty

recogni-on

event
extrac-o...

Impact
of
text
mining

•  Discovery
of
concepts
and

named
en--es
(anatomical

en--es...

•  Na-onal
Centre
for
Text
Mining,
School
of

Computer
Science

www.nactem.ac.uk

...

Mining
the
History
of
Medicine

Aim

Seman7c
search
system

•  Bri-sh
Medical
Journal
...

Mining
the
History
of
Medicine

Search
historical

archives

OCR

Keyword

search?

BMJ
...

Mining
the
History
of
Medicine

Solu-ons

ü  Apply
OCR
improvement
techniques

ü  Auto...

Mining
the
History
of
Medicine

Sema-c

search

system

ü  Automa-c
query
building,
...

Extrac-ng
seman-c
types,
events

ü  Our
text
mining
tools
learn
from
gold
standard

•...

OCR
Post
Correc-on

•  Re-‐OCR

BMJ
too
-me
consuming
for
current
project

•  Our
...

OCR
Post
Correc-on

ü Hunspell
produces
ranked
list
of
spelling
correc-ons

ü However,
...

JOHN MILLER, aged 26, glass-blower of Gateshead, was
adnmitted August 27th, 1840, unider the care of Sir John
Fife, with t...

Basic
Hunspell
Output

JOHN MILLER, aged 26, glass-blower of Gateshead, was
admitted August 27th, 1840, under...

New
Frequency-‐driven
Hunspell
Output

JOHN MILLER, aged 26, glass-blower of Gateshead, was
admitted August 2...

Avoiding
Over-‐Correc-on

Original
Text
Basic
Hunspell
Frequency-‐
driven
Hunspell

Freque...

Extrac-ng
seman-c
types,
events

ü  Our
text
mining
tools
learn
from
gold
standard

•...

Hymera
corpus:
En-ty
Types

Type
Descrip7on
Examples

Anatomical
An
en-ty
forming
par...

Hymera
Corpus:
Events

Type
Descrip7on
Par7cipants

Aﬀect
A
en-ty
or
event
is
aﬀect...

Hymera
Corpus:
Events

Type
Descrip7on
Par7cipants

Cause
An
en-ty
or
event
results
...

•  Trained
classiﬁers
on
Hymera
corpus

•  Used
dic-onaries
to
obtain
domain
speciﬁc
...

UMLS
è Corpus
Mappings

MetaMap
Categories
Hymera
category

Anatomical
Abnormality,
Body
S...

Seman-c
En--es:
Summary

ü  Even
baseline
system
produces
good
performance
on

most
...

Event
Recogni-on

•  Detects
“trigger”
phrases
around
which

events
are
arranged:
origin
...

Event
Recogni-on
Summary

ü  Complex
task

•  600
Aﬀect
and
200
Causality
events

ü...

Interpre-ng
events

ü Discourse
context
(meta-‐knowledge)
aﬀects

interpreta-on

•  p21ras...

Terminological
Issues

ü  Concepts
can
be
expressed
in
many
ways

ü  We
take
i...

Building
a
Time
Sensi-ve

Terminological
Resource

ü  Why
not
using
exis-ng
resources? ...

0

10

20

30

40

50

60

1840

1844

1848

1852

1856

1860

1864

1868

18...

Term
Varia-on
in
BMJ

Scarlet
Fever
vs.
Scarla:na

0

10

20

30

40

5...

Time
Sensi-ve
Medical
Terminological

Inventory

ü  We
have
created
a
#me
sensi#ve
termi...

Processing
Historical
Lexica

19th
century
medical
lexica
NLM
Archive

Two
lists
of
...

•  English
main

term

•  La-n
main
term

•  Synonym
list

•  Sub-‐type

English
term

•...

Processing
Historical
Lexica

ü Link
synonym
set
to
UMLS
using
approximate
string

match...

TM
Methods
for
Historical
Variant

Iden-ﬁca-on

ü  Pre-‐processing

ü  Distribu-onal
simil...

Dic-onary

matching

Machine

learning

Pre-‐Processing
BMJ

We
combined
two

recognisers

...

ü cosine
similarity

scarlet
fever
47366.48
46344.15
30555.26
31896.95

1524...

Distribu-onal
Similarity
Measures

scarlet
fever

scarla-na

0.8434

whooping
c...

Access
“query
builder”
to

start
search
reﬁnement

40

User
can
reﬁne
search
using

mul-ple
criteria.
Here
we

start
by
searching

for
...

User
enters
term
of
interest

and
then
clicks
on
“Reﬁne

Search”

42

Retrieved
documents

related
terms

User
selects
“pulmonary

tuberculosis”

Current
search
c...

“pulmonary

tuberculosis”
is
added
to

query
builder

composite
-me
graph

(automa-cally...

Further
reﬁne
retrieved

documents
by
date

published

45

Only
retain
documents

published
up
un-l
1950

46

Further
reﬁne
retrieved

documents
by
date

published

47

Reﬁne
by
automa-cally

recognised
seman-c

en--es

48

Sema-c
reﬁnement
can

be
made
according
to

diﬀerent
en-ty

categories

49

Here
“Environmental”

en--es
present
in
the

current
document
set,

with
their
counts.
...

New
sema-c
restric-on

added
to
query
builder

display

Number
of
documents

further
r...

Results
can
also
be

reﬁned
by
searching
for

documents
containing

involving
en--es

...

User
can
choose

between
the
2

events

recognised
by

our
system

53

User
(par-ally)

completes
template

according
to
the
types

of
events
they
are

searc...

Document
display

Bibliographic
informa-on

Document
content

Seman-c
informa-on

55

Pie
chart
shows
the
distribu-on
of

en-ty
types
in
a
document.

Hovering
the
mouse ...

Number
of

“Environmental”
en--es

in
the
document

“Environmental”
en-ty

instances
in
t...

Cases
where
speciﬁc
causes

of
tuberculosis
are

men-oned
in
the
document

Phrases
ide...

Aﬀect
events
allow
us
to

explore,
e.g.,
whether

therapeu-c
measures

have
a
posi-ve ...

Future
developments

ü  More
en7ty
types:

•  Tools
and
materials
used
in
a
...

Future
Developments
-‐
Aiributes

Recogni-on
of
aiributes
at
both
the
en-ty ...

Conclusions

ü Explore
further
archives
using
topic
analysis

ü Automa-c
clustering
of
...

•  BMJ
and
Wellcome
Library
for
making
the
archives

available
to
text
mine

•  AHRC
...

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