medigrid – sharing credible knowledge and reliable resources kryštof slabý, petr lesný...

MediGrid

– sharing credible knowledge and reliable resources

Kryštof Slabý, Petr Lesný

University Hospital Motol, Prague

krystof.slaby@lfmotol.cuni.cz

MediGrid

Documenting and implementing biomedical computations in the network environment

Utilizing the GRID distributed networking concepts

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Documentation goals Maximize reusability of the algorithms

SearchTrust

Allow interoperability of the algorithmsData identity

Provide basis for future publishing of new algorithmsPeer reviewed publicationConnection to established resources

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Implementation goals

Usable both on local computer and in network environment

Distributed and reusable Possibility of automated workflow

construction Security, Accounting, Access control

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MediGrid: current status

Developed general mechanisms of documentation

Documented algorithms from biomedical domains:Paediatric auxologyNephrologyPulmonary function testsDNA diagnostics

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Contents Introduction

Documentation of medical algorithms

Trust

Phenomenological Description of Biomedical Data

Grid Networking Closing remarks

„Sharing knowledge in biomedicine“

Evidence Basedness

Workflow

Ad-hoc ontology

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Sharing knowledge

What You share? Formalized description

How do You find it? Ontology

Do You trust author? Review No => References to literature

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Formalized description

administrative (title, author, date published etc.)

„syntax“ (datatype, range, input, output)

„semantic“ (description, references, method of measurement, units ...)

technical (WS address, unittests)

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Ontology

later

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Knowledge lifecycle

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Publication

Formal criteria Review

Proper description Evidence based (references)

Responsibility author, reviewer, EBM

Formalized Computer processable, not understandable

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Evidencebasedness

Knowledge expressed Literature based

How solid is the basis?

Relation of referenced to description Quality of description

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Documenting of medical algorithms

Is it really so different?

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Algorithmic medicine

ComputationsDose_of_drug = Dose_per_kg × Weight_kg

ScoresE.g. Glasgow coma scale

Guidelines If high glucose, then examine blood K+ level

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Pros and Cons

GoodObjectivization helps young M.D.s to deal with

complicated situationsCan simulate „expert opinion“Can be automated (saves time)

BadMust be utilized in proper clinical situationGarbage in – garbage outCan „dehumanize“ medicine

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Documentation

Human readableDescription, Argumentation, …Semantics („meaning of the data“)

Human and computer readableLinks to external entities, …

Computer readableSyntax of input and output dataConstruction of user interface…

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Documentation

Algorithms and Input and output data

BMI = weight / height2

1. Body mass index

2. Body weight

3. Body height

4. The BMI calculation

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Documenting algorithms

Name, author, abstract, definitions of terms List of inputs and outputs Method of computation or processing Supportive and Controversial expert opinions Restrictions References to peer-reviewed journals Classification systems – UMLS, MeSH

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Documenting inputs and outputs

Name, author, abstract, definitions of terms

Precision, Interpretation Controversy Origin of data, Measurement References to peer-reviewed journals Classification systems – UMLS, MeSH

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Documenting inputs and outputs

1. BSA = 4.688 * ((weight) ^ (0.8168 – (0.0154 * log10 (weight)))) [Boyd, 1935]

2. BSA = 3.207 * ((height)^(0.3)) * ((weight) ^ (0.7285 - (0.0188 * log10 (weight)))) [Milazzo, 1985]

3. Drug_dose = BSA * dose_per_sq_m [Drug data sheet]

Can be the result of (1) or (2) utilized in (3)?

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Documentation service

Set of documentation – algorithms and their inputs and outputs

Centralized × Distributed

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Trust

Do you trust me?

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„Trust“ in science

Implicit concept of Scientific method in biosciences

Basic levels of trust Highest: What I have personally experimented with Very high: Information from textbooks ;-) High: Publications in peer-reviewed journals Middle: Reviews in peer-reviewed journals Lower: Publications in other scientific journals Low: Posters etc.

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„Trust“ in science

ModificationsTrust / Distrust in Someone [‘s work]Delegation of trustRelation to my own experiments

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Trust: Documentation

Documentation must be reliable1. Peer-review systém of experts

2. Connection to peer-reviewed journals

3. Possibility of trust delegation

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Trust: Implementation

We work with patients‘ data

Network layer (e.g. SSL)Do we communicate with the right computer?

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Modules

= relations among entities some computable

weight & height => BMI => obesity

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Workflow

Encapsulates multiple modules Same interface as single module Static/dynamic construction Workflow editor

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Example of complex workflow

BP < NIBP

MAP

MAP

RR detector

PEP < BPPEP

BPS/BPD

Inst. fH

ECG

MAP estimate

HR

HR

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Phenomenological Description of Biomedical Data

Indicators versus data.

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What is the problem?

BMI = weight / height2

Is it possible to document the „semantics“ of these data?Body mass indexBody weightBody height

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Semantic web approach

Define complex „ontology“unit of measurementrelations to body functions and dimensions is_a, is_part_of, …

InstrumentsProtégé, OWL, PROLOG

ExamplesBody weight in kg is_a body weightBody weight in lb is_a body weight

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Semantic web problem

Biomedical data are too complex

Is it really „semantic?“Will the computer understand, what does it

mean to be overweight?

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Biomedical data as indicators

Phemomenological approach [Husserl]

“A thing is... properly an indication if and where it in fact serves to indicate something to some thinking being... a common circumstance [is] the fact, that certain objects or states of affairs of whose reality someone has actual knowledge indicate to him the reality of certain other objects or states of affairs, is the sense that his belief in the reality of the one is experienced (...) as motivating a belief or surmise in the reality of the other.” [Italics by E. H.].

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Indicators

The reading of text „Height 190 cm“ evokes in the reader (indicates) quite tall person

Can be transformed Height 190 cm Taller than average

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Transformations

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Indicator ontology

Indicators can be grouped into „Indicator classes“ based on their common role in transformations (all recognizable indicators informing reader about body height)

Indicators can be transformed to other indicators manually or using computers

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Indicator ontology

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Ontologies to date

MeSH, UMLS, SNOMED, ICD etc.

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Ad-hoc ontology

Computer understandable syntactic information (module = relation)

Computer processable semantic information

Aposteriori constructed ontology

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GRID networking

And S.E.T.I. at home?

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Service oriented architecture

Service oriented architectureAgents (computer or human)Emphasis on actionsAgent communication through message

exchange

A service is a set of actions that form a coherent whole from the point of view of service providers and service requesters

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Web services architecture

Follows the SOA concepts

Emphasis on interoperabilityXML, XML, XMLProgramming model, implementation

technology, operating systém unaware

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Distributed computing Physically distributed services and data Local (LAN) or large scale (WAN) Paralell computing Resource sharing

CPU time Peripherals – printers etc. Data

Application1. Large performance required2. Integration of resources

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GRID

Large diversity of distributed (physical) resources

Access is globally unified through virtual layers (unifying abstractions)

ApplicationsComputational GridsScientific Data GridsVirtual Organizations Information and Knowledge Services

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Grids

Stress on security issues (suitable for patient data processing?)

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Conclusions

Documentation of biomedical algorithms is not yet well established Medigrid documentation service

Description of biomedical data in current classifications and ontologies is limited Indicator Ontology

Implementations are not reliably documented and therefore are not reusable GRID networking

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Next?

No.