mobile information retrieval in medicine: a semantic ... · mobile information retrieval in...

Mobile Information Retrieval in Medicine:A Semantic Approach

(Short Communication)

Markus Kreuzthaler1, Marcus Bloice1,Lukas Faulstich2,

Klaus-Martin Simonic1, Andreas Holzinger1

1Institute for Medical Informatics Statistics and Documentation,Medical University of Graz, Austria

2ID Information und Dokumentation im Gesundheitswesen GmbH & Co.KGaA (ID),Berlin, Germany

MIE Conference, August 31, 2011, Oslo

Markus Kreuzthaler (IMI) Mobile IR MIE 2011 1 / 14

Mobile Information Retrieval

Mobile Information Retrieval differs in two main aspects to classicalInformation Retrieval:

Context AwarenessBy exploiting the sensors within a mobile device, Context Awarenesstries to be aware of the user’s situation.

Content AdaptationContent Adaptation addresses the visualization of the results of aninformation need to the mobile device.

Markus Kreuzthaler (IMI) Mobile IR MIE 2011 2 / 14

Mobile Information Retrieval

Mobile Information Retrieval differs in two main aspects to classicalInformation Retrieval:

Context AwarenessBy exploiting the sensors within a mobile device, Context Awarenesstries to be aware of the user’s situation.

Content AdaptationContent Adaptation addresses the visualization of the results of aninformation need to the mobile device.

Markus Kreuzthaler (IMI) Mobile IR MIE 2011 2 / 14

Mobile Information Retrieval

Mobile Information Retrieval differs in two main aspects to classicalInformation Retrieval:

Context AwarenessBy exploiting the sensors within a mobile device, Context Awarenesstries to be aware of the user’s situation.

Content AdaptationContent Adaptation addresses the visualization of the results of aninformation need to the mobile device.

Markus Kreuzthaler (IMI) Mobile IR MIE 2011 2 / 14

Project Evolution SIXMIInitial project:

A doctor is confronted with a lot of documents belonging to apatient.Tag those that belong to the class of inflammation or neoplasm.A solution to this is a rule based approach to classify thesedocuments.

Follow-up project:

Semantic Information Extraction in Medical Information SystemsEvaluation of an information retrieval tool developed by ID.Statistical evaluation measure for unranked retrieval results:

I Precision, Recall, Fallout, F1-Measure

Comparing the information retrieval tool with a human expert.

Markus Kreuzthaler (IMI) Mobile IR MIE 2011 3 / 14

Project Evolution SIXMIInitial project:

A doctor is confronted with a lot of documents belonging to apatient.Tag those that belong to the class of inflammation or neoplasm.A solution to this is a rule based approach to classify thesedocuments.

Follow-up project:

Semantic Information Extraction in Medical Information SystemsEvaluation of an information retrieval tool developed by ID.Statistical evaluation measure for unranked retrieval results:

I Precision, Recall, Fallout, F1-Measure

Comparing the information retrieval tool with a human expert.

Markus Kreuzthaler (IMI) Mobile IR MIE 2011 3 / 14

SIXMI ExampleInformation NeedReport all observation reports which refer to an intestinal neoplasm.

Search Request IR Tool : neubildung, darm [=neoplasm, intestine]Search Request Expert :

Intestine NeoplasmExpression Syntax Terms to hit Expression Syntax Terms to hit

%kolon%,%colon%

Kolon, Colon %karzinom% Karzinom

%re_t% Rektum, Rectum %adenom% Adenom%sigm% Sigmoideum %kar_inoid% karzinoid, karcinoid%duoden% Duodenum %car_inoid% carzinoid, carcinoid%jejun% Jejunum %lymphom% Lymphom%hemi_olektomie% Hemikolektomie,

Hemicolektomie%sar_om% Sarkom, Sarcom

%ileum% Ileum %myom% Myom%ileo% Ileo %neurom% Neurom%appendix% Appendix %tumor% Tumor%coe_um% Coecum, Coekum %neuroendokrin% neuroendokrin%zoe_um% Zoekum, Zoecum %intraepithel% intraepithel

%neoplasie% Neoplasie%NHL% Non-Hodgkin Lymphoma

Markus Kreuzthaler (IMI) Mobile IR MIE 2011 4 / 14

SIXMI ExampleInformation NeedReport all observation reports which refer to an intestinal neoplasm.

Search Request IR Tool : neubildung, darm [=neoplasm, intestine]

Search Request Expert :

Intestine NeoplasmExpression Syntax Terms to hit Expression Syntax Terms to hit

%kolon%,%colon%

Kolon, Colon %karzinom% Karzinom

%re_t% Rektum, Rectum %adenom% Adenom%sigm% Sigmoideum %kar_inoid% karzinoid, karcinoid%duoden% Duodenum %car_inoid% carzinoid, carcinoid%jejun% Jejunum %lymphom% Lymphom%hemi_olektomie% Hemikolektomie,

Hemicolektomie%sar_om% Sarkom, Sarcom

%ileum% Ileum %myom% Myom%ileo% Ileo %neurom% Neurom%appendix% Appendix %tumor% Tumor%coe_um% Coecum, Coekum %neuroendokrin% neuroendokrin%zoe_um% Zoekum, Zoecum %intraepithel% intraepithel

%neoplasie% Neoplasie%NHL% Non-Hodgkin Lymphoma

Markus Kreuzthaler (IMI) Mobile IR MIE 2011 4 / 14

SIXMI ExampleInformation NeedReport all observation reports which refer to an intestinal neoplasm.

Search Request IR Tool : neubildung, darm [=neoplasm, intestine]Search Request Expert :

Intestine NeoplasmExpression Syntax Terms to hit Expression Syntax Terms to hit

%kolon%,%colon%

Kolon, Colon %karzinom% Karzinom

%re_t% Rektum, Rectum %adenom% Adenom%sigm% Sigmoideum %kar_inoid% karzinoid, karcinoid%duoden% Duodenum %car_inoid% carzinoid, carcinoid%jejun% Jejunum %lymphom% Lymphom%hemi_olektomie% Hemikolektomie,

Hemicolektomie%sar_om% Sarkom, Sarcom

%ileum% Ileum %myom% Myom%ileo% Ileo %neurom% Neurom%appendix% Appendix %tumor% Tumor%coe_um% Coecum, Coekum %neuroendokrin% neuroendokrin%zoe_um% Zoekum, Zoecum %intraepithel% intraepithel

%neoplasie% Neoplasie%NHL% Non-Hodgkin Lymphoma

Markus Kreuzthaler (IMI) Mobile IR MIE 2011 4 / 14

SIXMI Result

Method Precision RecallDomain Expert 0.74 0.94Information Retrieval Tool 0.78 0.93

Table: Result Training Data (~500 diagnose texts).

Method Precision RecallDomain Expert 0.76 0.92Information Retrieval Tool 0.73 0.93

Table: Result Test Data (~3000 diagnose texts).

Markus Kreuzthaler (IMI) Mobile IR MIE 2011 5 / 14

SIXMI Result

Method Precision RecallDomain Expert 0.74 0.94Information Retrieval Tool 0.78 0.93

Table: Result Training Data (~500 diagnose texts).

Method Precision RecallDomain Expert 0.76 0.92Information Retrieval Tool 0.73 0.93

Table: Result Test Data (~3000 diagnose texts).

Markus Kreuzthaler (IMI) Mobile IR MIE 2011 5 / 14

Mobile Information Retrieval (2)

Semantic Retrieval ToolQuery complexity is shifted to a powerful semantic retrieval logic.Short intuitive queries.

Short user input supports the mobile information need behavior.

Proof of ConceptMobile Information Retrieval Environment.

Markus Kreuzthaler (IMI) Mobile IR MIE 2011 6 / 14

Mobile Information Retrieval (2)

Semantic Retrieval ToolQuery complexity is shifted to a powerful semantic retrieval logic.Short intuitive queries.

Short user input supports the mobile information need behavior.

Proof of ConceptMobile Information Retrieval Environment.

Markus Kreuzthaler (IMI) Mobile IR MIE 2011 6 / 14

Mobile Information Retrieval (2)

Semantic Retrieval ToolQuery complexity is shifted to a powerful semantic retrieval logic.Short intuitive queries.

Short user input supports the mobile information need behavior.

Proof of ConceptMobile Information Retrieval Environment.

Markus Kreuzthaler (IMI) Mobile IR MIE 2011 6 / 14

Mobile Information Retrieval Architecture

Client

Search

User

User

User

Markus Kreuzthaler (IMI) Mobile IR MIE 2011 7 / 14

Mobile Information Retrieval Architecture

ClientSearch Engine Wrapper

Tomcat Server

SearchSe

arch

Con

trolle

rThe ID SemanticRetrieval Tool

User

User

UserSp

ring

MVC

Markus Kreuzthaler (IMI) Mobile IR MIE 2011 8 / 14

Mobile Information Retrieval Architecture

ClientSearch Engine Wrapper

Tomcat Server

Search

Text Repository

Sear

ch C

ontro

ller

The ID SemanticRetrieval Tool

Linguistic Analysis andSemantic Representation

Knowledge Base

User

User

UserSp

ring

MVC

Markus Kreuzthaler (IMI) Mobile IR MIE 2011 9 / 14

Result

Markus Kreuzthaler (IMI) Mobile IR MIE 2011 10 / 14

Result

Markus Kreuzthaler (IMI) Mobile IR MIE 2011 11 / 14

Research Outline

Most importantIdentify meaningful use cases for mobile information access inmedicine:

Emergency situations.Teaching.Mobile data aggregation of patients.

Design of search user interfaces

I Use of other input methods instead of typing.I Use of Context Awareness to shrink down the information space.

Markus Kreuzthaler (IMI) Mobile IR MIE 2011 12 / 14

Research Outline

Most importantIdentify meaningful use cases for mobile information access inmedicine:

Emergency situations.Teaching.Mobile data aggregation of patients.

Design of search user interfacesI Use of other input methods instead of typing.I Use of Context Awareness to shrink down the information space.

Markus Kreuzthaler (IMI) Mobile IR MIE 2011 12 / 14

Research Outline, Emergency

Emergency reference -Shirt pocket sized.

Standard for emergencydoctors and medics inAustria.Maximum comprised data,clearly arranged for theuser in the emergency usecase.10th edition, ~65,000copies sold.

Markus Kreuzthaler (IMI) Mobile IR MIE 2011 13 / 14

Research Outline, Emergency

Emergency reference -Shirt pocket sized.Standard for emergencydoctors and medics inAustria.

Maximum comprised data,clearly arranged for theuser in the emergency usecase.10th edition, ~65,000copies sold.

Markus Kreuzthaler (IMI) Mobile IR MIE 2011 13 / 14

Research Outline, Emergency

Emergency reference -Shirt pocket sized.Standard for emergencydoctors and medics inAustria.Maximum comprised data,clearly arranged for theuser in the emergency usecase.

10th edition, ~65,000copies sold.

Markus Kreuzthaler (IMI) Mobile IR MIE 2011 13 / 14

Research Outline, Emergency

Emergency reference -Shirt pocket sized.Standard for emergencydoctors and medics inAustria.Maximum comprised data,clearly arranged for theuser in the emergency usecase.10th edition, ~65,000copies sold.

Markus Kreuzthaler (IMI) Mobile IR MIE 2011 13 / 14

Acknowledgments and References

ID Information und Dokumentation im GesundheitswesenGmbH & Co.KGaA (ID), Berlin, Germany.

A. Holzinger and M. Errath.Mobile computer web-application design in medicine: someresearch based guidelines.Universal Access in the Information Society, 6(1):31–41, 2007.

F.S. Tsai, M. Etoh, X. Xie, W.C. Lee, and Q. Yang.Introduction to mobile information retrieval.IEEE Intelligent Systems, 25(1):11–15, 2010.

Markus Kreuzthaler (IMI) Mobile IR MIE 2011 14 / 14