““Victor Babes” Victor Babes” UNIVERSITY OF MEDICINE UNIVERSITY OF MEDICINE

AND PHARMACY AND PHARMACY TIMISOARATIMISOARADEPARTMENT OFDEPARTMENT OF

MEDICAL INFORMATICS AND BIOPHYSICSMEDICAL INFORMATICS AND BIOPHYSICS

Medical Informatics DivisionMedical Informatics Divisionwww.medinfo.umft.ro/dimwww.medinfo.umft.ro/dim

2007 / 20082007 / 2008

COURSE 1COURSE 1

1. MEDICAL INFORMATICS

MEDICAL INFORMATICSMEDICAL INFORMATICS – an interdisciplinary field studying:

Old definition: computer applications in medical practice and research

Modern definition: generation, acquisition, storage, transmission, processing, protection and use of medical information

2. 2. INFORMATION INFORMATION THEORYTHEORY

2.1. INTRODUCT2.1. INTRODUCTORY NOTIONSORY NOTIONS

• a) VARIABLES a) VARIABLES – deterministicdeterministic

• well defined values• by repeating the measurement the same values

will be obtained – random random (stochastic)(stochastic)

• get different values even will keep the conditions

• ex: throwing the dice, tossing a coin

• b) PROBABILITY:b) PROBABILITY:– EVENT = EXPERIMENT’S RESULTEVENT = EXPERIMENT’S RESULT– FREFREQENCESQENCES::

• ABSOLUTE - nABSOLUTE - nii

• RELATIVE - nRELATIVE - nii / N, / N, n nii = N = N

– FIELD OFFIELD OF EVENTS:EVENTS:• EVENEVENTTSS XX11 X X22 . . . X . . . Xkk

• ABS.FREQ.ABS.FREQ. nn11 n n22 . . . n . . . nkk

– DEFINITION OF PROBABILTY:DEFINITION OF PROBABILTY:)/(lim Nnp i

Ni

EXAMPLESEXAMPLES

c) c) FIELD OFFIELD OF PROBABILIPROBABILITTIESIES:: - - EVENTS X1 X2 . . . Xk

- PROBABILITIES p1 p2 . . . pk

TTYYPPESES OF EVENTS: OF EVENTS: - - certain event - - - - p = 1 - impossible event - - - p = 0 - equelprobabile events pi = pj

2.2. NOTION OF INFORMATION2.2. NOTION OF INFORMATION

• a) Definition: a) Definition: philosophical categoryphilosophical category ( (with high with high degree of generality) defineddegree of generality) defined byby proper properttiesies::Basic propertyBasic property::‘‘REMOVING AN UNCERTAINTY’REMOVING AN UNCERTAINTY’

• b) Information nature:b) Information nature:– it’s not substance– it’s not energy

• c) Cc) Completeomplete approach (triadic) approach (triadic)::– matter structure– Energy support– information (function)

• d) d) Utility valueUtility value ofof information information– depends on the receptor– examples

2.3. 2.3. AMOUNT OF AMOUNT OF INFORMATIINFORMATIONON

• a) a) FOR ONEFOR ONE EVENT (Shannon) EVENT (Shannon)

IIii = log = log22 (1/p (1/pii) = - log) = - log22 p pii

• b) UNITb) UNIT of measure of measure: BIT (Binary digIT):: BIT (Binary digIT):1 bit 1 bit removes an uncertaintyremoves an uncertainty of of 1/2 1/2

c) INFORMATIONALc) INFORMATIONAL ENTROPY ENTROPY

• AVERAGE INFORMATION OF ONEAVERAGE INFORMATION OF ONE EVENTEVENT IN A MESSAGE OF LENGTH “N” IN A MESSAGE OF LENGTH “N”

IImm = (n = (n11II1 1 + . . . + n+ . . . + nkkIIkk) / N) / N

IImm = H = = H = p piiIIii

H = - H = - p pi i loglog2 2 ppii

d) d) FORFOR EQUIPROBABLE EQUIPROBABLE EVENTEVENTSS

ppii = 1 / k , H = H = 1 / k , H = Hmaxmax = log = log22 k k

e) Examples: e) Examples: oonene proteic proteic sesequencequence of of 100 amino acids100 amino acids

k = 20 aa , p = 1 / 20k = 20 aa , p = 1 / 20 H = 20 ( (1/20) logH = 20 ( (1/20) log22 (1/20) ) = 4,5 bit/aa (1/20) ) = 4,5 bit/aa IItottot = 100 x 4,5 = 450 bit = 100 x 4,5 = 450 bit

f) The relation with the thermodynamic f) The relation with the thermodynamic entropentropyy andand order order ((MMaxwell’s demonaxwell’s demon))

2.4. REDUNDANCY2.4. REDUNDANCY• a) DEFINITION:a) DEFINITION:

- - ABSOLUTEABSOLUTE REDUNDANCY REDUNDANCY

R = HR = HMAXMAX - H - HREALREAL

- - RELATIVRELATIVE REDUNDANCYE REDUNDANCY

RRrr = R / H = R / HMAXMAX • b) UTILITY: to decrease b) UTILITY: to decrease perturbations perturbations efeffefectctss

iin n the information transfer processthe information transfer process

2.5. COMMUNICAT2.5. COMMUNICATIION ON SSYYSTEMSTEMSS

• a) DEFINITIONS:a) DEFINITIONS:MESSAGE = the informationMESSAGE = the information which which isis transmittedtransmittedSSIGIGNAL = the physical support forNAL = the physical support for the the messagemessage

b) THE COMMb) THE COMMUNICAUNICATIONTION SSYYSTEM SCHEMSTEM SCHEMEE

S = source (S = source (ememmitter)mitter)R = destination (receptor)R = destination (receptor)C = communication channelC = communication channelN = perturbations (noise)N = perturbations (noise)

c) TRANSDUCERS = device c) TRANSDUCERS = device which which chachangngees s d) MODEMS = MOdulation / DEModulationd) MODEMS = MOdulation / DEModulatione) CODIe) CODINGNG = = tratranslationnslation fromfrom one alphabet one alphabet toto anotheranotherf) THE CHANNEL f) THE CHANNEL CAPACITCAPACITYY = bits/seconds = bits/seconds (bps,baud)(bps,baud)

2.6. INFORMATION TRANSFER IN 2.6. INFORMATION TRANSFER IN BIOLOGICAL BIOLOGICAL SSYYSTEMSTEMSS

a) a) THETHE GENETIC CODE: GENETIC CODE: DNA, 4 baDNA, 4 basesses (A - T / U, C - G) (A - T / U, C - G) REPLICATION, CODONSREPLICATION, CODONS b) b) CODICODINGNG IIN N NERVOUS NERVOUS SSYYSTEMSTEM

- FRE- FREQUENCYQUENCY - ON - ON AXONSAXONS - AMPLITUDE - DENDRITES, S- AMPLITUDE - DENDRITES, SYYNAPSESNAPSES

c) EXTERNAL INFORMATION - c) EXTERNAL INFORMATION - sensesense organs organs d) d) IINTERNAL INFORMATION - interorceptorsNTERNAL INFORMATION - interorceptors

3.3. MEDICAL MEDICAL INFORMATIONINFORMATION

3.1. MEDICAL INFORMATION3.1. MEDICAL INFORMATION• PACIENT – PHYSICIAN RELATIONPACIENT – PHYSICIAN RELATION• ELEMENTARY CYCLE OF MEDICAL ELEMENTARY CYCLE OF MEDICAL

ACTIVITYACTIVITY• MEDICAL INFORMATION USED IN MEDICAL INFORMATION USED IN

MEDICAL ACTIVITY:MEDICAL ACTIVITY:– DATA – individualDATA – individual character character - fa- faccttss– KNOWLEDGE – generalKNOWLEDGE – general character character - concept- conceptss

3.2. 3.2. ELEMENTARY CYCLE OF MEDICAL ACTIVITY

3.3. Medical Information Classification3.3. Medical Information Classificationon Structural Levelson Structural Levels

Level of Level of medical medical

informationinformation

Structural Structural levellevel

Studied by:Studied by: DomainDomain Chapter Chapter in IMin IM

Infra-individual

level

Molecular / Molecular / subcellularsubcellular

Molecular Biology and Molecular Biology and GeneticsGenetics

  

LifeLifeSciencesSciences

BioinformaticsBioinformatics

Cell / tissueCell / tissue Cell BiologyCell Biology

Organ /Organ /SystemSystem

PhysiologyPhysiologyNeuro Neuro --

informaticsinformaticsBrain TheoryBrain Theory

CognitiveCognitiveSciencesSciences

Individuallevel

Whole Whole organismorganism(‘pacient’)(‘pacient’)

Paraclinical Disciplines Paraclinical Disciplines (investigations)(investigations)

Clinical Disciplines Clinical Disciplines (diagnosis, treatment)(diagnosis, treatment)

MedicalMedicalSciencesSciences

Clinical Clinical InformaticsInformatics

Supra-individual

level

CommunityCommunity Public HealthPublic Health  

HealthHealthSSciencesciences

  

HealthHealthInformaticsInformaticsHealthcareHealthcare

ActivityActivityHealthcareHealthcare

ManagementManagement

3.4. 3.4. TYPES OF DATA

• QUALITATIVE – Anamnesis (descriptive)QUALITATIVE – Anamnesis (descriptive)• NUMERICAL – Laboratory investigationsNUMERICAL – Laboratory investigations• GRAPHICAL – Biosignals (ECG, EEG…)GRAPHICAL – Biosignals (ECG, EEG…)• SOUNDS: PhonocardiogramSOUNDS: Phonocardiogram• STATIC IMAGES: X-Ray, NMRSTATIC IMAGES: X-Ray, NMR• DYNAMIC IMAGES – moviesDYNAMIC IMAGES – movies

3.5. 3.5. Operations with information

- Generation (biomedical process or action)- Acquisition (collection) – depends on

information nature- Storage – data bases, knowledge bases- Processing – for interpretation- Transmission- Protection- Use

4.4. CHAPTERS OF CHAPTERS OF MEDICAL INFORMATICS MEDICAL INFORMATICS

Ist PARTIst PART. DATA. DATA– STORAGE - DATABASES– ACQUISITION & PROCESSING:

• NUMERICAL & QUALITATIVE – BIOSTATISTICS• SIGNAL PROCESSING, MEDICAL IMAGING

IInd PARTIInd PART. MEDICAL KNOWLEDGE. MEDICAL KNOWLEDGE– MEDICAL DECISION SUPPORT– EXTRACTION & FORMALIZATION OF MEDICAL

KNOWLEDGE

IIIrd PART. IIIrd PART. HEALTHCARE INFORMATICSHEALTHCARE INFORMATICS– INFORMATION SYSTEMS

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