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Negation Detection in Swedish Clinical Text Maria Skeppstedt PhD Student at Stockholm University Department of Computer and Systems Sciences
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Negation Detection in Swedish Clinical Text Maria Skeppstedt PhD Student at Stockholm University Department of Computer and Systems Sciences.

Dec 11, 2015

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Page 1: Negation Detection in Swedish Clinical Text Maria Skeppstedt PhD Student at Stockholm University Department of Computer and Systems Sciences.

Negation Detection in Swedish Clinical Text

Maria Skeppstedt

PhD Student atStockholm University

Department of Computer and Systems Sciences

Page 2: Negation Detection in Swedish Clinical Text Maria Skeppstedt PhD Student at Stockholm University Department of Computer and Systems Sciences.

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Why do you need negation detection in clinical text?

Page 3: Negation Detection in Swedish Clinical Text Maria Skeppstedt PhD Student at Stockholm University Department of Computer and Systems Sciences.

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Record X

Since the patient has

no headache, the

patient does probably

not have disease A.

Record Y

The patient has a

headache.

Page 4: Negation Detection in Swedish Clinical Text Maria Skeppstedt PhD Student at Stockholm University Department of Computer and Systems Sciences.

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A first step towards Swedish negation detection

Page 5: Negation Detection in Swedish Clinical Text Maria Skeppstedt PhD Student at Stockholm University Department of Computer and Systems Sciences.

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NegEx

By Wendy W Chapman, Will Bridewell, Paul Hanbury, Gregory F. Cooper, and Bruce G. Buchanan

Page 6: Negation Detection in Swedish Clinical Text Maria Skeppstedt PhD Student at Stockholm University Department of Computer and Systems Sciences.

Basic idea of NegEx

Maria Skeppstedt, Louhi'10

Since the patient has no headache, … (headache)

The patient has not only a headache, but also … (headache)

Pre-Triggers

no

not

no signs of

Post-Triggers

unlikely

Pseudo negation

not only

Page 7: Negation Detection in Swedish Clinical Text Maria Skeppstedt PhD Student at Stockholm University Department of Computer and Systems Sciences.

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Translation of negation triggers

• no ->ingen

• not -> inte

• no signs of -> inga tecken

• …

• not only -> inte bara

• …

Page 8: Negation Detection in Swedish Clinical Text Maria Skeppstedt PhD Student at Stockholm University Department of Computer and Systems Sciences.

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Grammatical differences, Swedish and English, examples

1. Gender and number concord: ”no’’ -> ”inga” (plural), ”ingen” (common gender) and ”inget” (neuter gender)“no significant” -> ”inga signifikanta” (plural), “ingen signifkant” (common gender) and “inget signifikant” (neuter gender)

2. ”denies/is denying” -> no grammatical equivalent in Swedish

Page 9: Negation Detection in Swedish Clinical Text Maria Skeppstedt PhD Student at Stockholm University Department of Computer and Systems Sciences.

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Construction of test data

1. Diseases and symptoms from the describing text of the ICD-10 codes

2. Automatic pre-processing of ICD-10 codesFor example: “migraine, not specified” -> “migraine”

Page 10: Negation Detection in Swedish Clinical Text Maria Skeppstedt PhD Student at Stockholm University Department of Computer and Systems Sciences.

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Classification of test data

1. 430 sentences

2. Affirmed, negated and ambiguous

Page 11: Negation Detection in Swedish Clinical Text Maria Skeppstedt PhD Student at Stockholm University Department of Computer and Systems Sciences.

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Results, group 1, sentences with trigger phrases

Page 12: Negation Detection in Swedish Clinical Text Maria Skeppstedt PhD Student at Stockholm University Department of Computer and Systems Sciences.

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Results, group 2, sentences without trigger phrases

Page 13: Negation Detection in Swedish Clinical Text Maria Skeppstedt PhD Student at Stockholm University Department of Computer and Systems Sciences.

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Triggers for correctly identified negations

Page 14: Negation Detection in Swedish Clinical Text Maria Skeppstedt PhD Student at Stockholm University Department of Computer and Systems Sciences.

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Precision for different triggers

Page 15: Negation Detection in Swedish Clinical Text Maria Skeppstedt PhD Student at Stockholm University Department of Computer and Systems Sciences.

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Examples of errors, that account for some of the difference

1. ”inga egentliga märkbara symptom …” (no real noticeable symptoms …)

2. ”Hon har inte huvudvärk, utan tandvärk ” (She has not headache, but toothache)

3. ”icke allergisk astma” (non-allergic asthma)

Page 16: Negation Detection in Swedish Clinical Text Maria Skeppstedt PhD Student at Stockholm University Department of Computer and Systems Sciences.

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Examples of other errors

1. ”Patienten har inte huvudvärk, men bröstsmär- tor.” (The patient has no headache, but chest pain)

2. ”Om inte huvudvärken har vikit ...” (If not the headache has disappeared)

3. ”Cirka hälften av alla med sjukdom A har inte symptom B” (About half of those with disease A, have no symptoms of B)

Page 17: Negation Detection in Swedish Clinical Text Maria Skeppstedt PhD Student at Stockholm University Department of Computer and Systems Sciences.

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The next step

1. A list of conjunctions that limit the scope of the trigger.

2. Elaborate with adding or removing trigger phrases from the list.

3. Evaluation on a larger test set.

4. Detect the meaning of “utan” (but/without) in the context, and which cases that the trigger “not” negates.

Page 18: Negation Detection in Swedish Clinical Text Maria Skeppstedt PhD Student at Stockholm University Department of Computer and Systems Sciences.

Thank you!

Questions?

Maria Skeppstedt

[email protected]