“Victor Babes” UNIVERSITY OF MEDICINE AND PHARMACY TIMISOARA DEPARTMENT OF MEDICAL INFORMATICS AND BIOPHYSICS Medical Informatics Division / 2006

COURSE 1

1. MEDICAL INFORMATICS MEDICAL INFORMATICS MEDICAL 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. INFORMATION THEORY 2. INFORMATION THEORY

2.1. INTRODUCTORY NOTIONS a) VARIABLESa) VARIABLES –deterministic well defined values by repeating the measurement the same values will be obtained –random (stochastic) get different values even will keep the conditions ex: throwing the dice, tossing a coin

b) PROBABILITY:b) PROBABILITY: –EVENT = EXPERIMENT’S RESULT –FREQENCES: ABSOLUTE - n iABSOLUTE - n i RELATIVE - n i / N,  n i = NRELATIVE - n i / N,  n i = N –FIELD OF EVENTS: EVENTS X 1 X 2... X kEVENTS X 1 X 2... X k ABS.FREQ.n 1 n 2... n kABS.FREQ.n 1 n 2... n k –DEFINITION OF PROBABILTY: EXAMPLES

c) FIELD OF PROBABILITIES: c) FIELD OF PROBABILITIES: - - EVENTS X 1 X 2... X k - PROBABILITIESp 1 p 2... p k TYPES OF EVENTS: TYPES OF EVENTS: - - certain event p = 1 - impossible event p = 0 - equelprobabile events p i = p j

2.2. NOTION OF INFORMATION a) Definition: philosophical category (with high degree of generality) defined by properties:a) Definition: philosophical category (with high degree of generality) defined by properties: Basic property: ‘REMOVING AN UNCERTAINTY’ b) Information nature:b) Information nature: –it’s not substance –it’s not energy

c) Complete approach (triadic):c) Complete approach (triadic): –matter structure –Energy support –information (function) d) Utility value of informationd) Utility value of information –depends on the receptor –examples

2.3. AMOUNT OF INFORMATION a) FOR ONE EVENT (Shannon)a) FOR ONE EVENT (Shannon) I i = log 2 (1/p i ) = - log 2 p i b) UNIT of measure: BIT (Binary digIT):b) UNIT of measure: BIT (Binary digIT): 1 bit removes an uncertainty of 1/2

c) INFORMATIONAL ENTROPY AVERAGE INFORMATION OF ONE EVENT IN A MESSAGE OF LENGTH “N”AVERAGE INFORMATION OF ONE EVENT IN A MESSAGE OF LENGTH “N” I m = (n 1 I n k I k ) / N I m = H =  p i I i H = -  p i log 2 p i

d) FOR EQUIPROBABLE EVENTS p i = 1 / k, H = H max = log 2 k p i = 1 / k, H = H max = log 2 k e) Examples: one proteic sequence of 100 amino acids e) Examples: one proteic sequence of 100 amino acids k = 20 aa, p = 1 / 20 k = 20 aa, p = 1 / 20 H = 20 ( (1/20) log 2 (1/20) ) = 4,5 bit/aa H = 20 ( (1/20) log 2 (1/20) ) = 4,5 bit/aa I tot = 100 x 4,5 = 450 bit I tot = 100 x 4,5 = 450 bit f) The relation with the thermodynamic entropy and order ( Maxwell’s demon ) f) The relation with the thermodynamic entropy and order ( Maxwell’s demon )

2.4. REDUNDANCY a) DEFINITION:a) DEFINITION: - ABSOLUTE REDUNDANCY R = H MAX - H REAL - RELATIVE REDUNDANCY R r = R / H MAX b) UTILITY: to decrease perturbations effects in the information transfer processb) UTILITY: to decrease perturbations effects in the information transfer process

2.5. COMMUNICATION SYSTEMS a) DEFINITIONS:a) DEFINITIONS: MESSAGE = the information which is transmitted SIGNAL = the physical support for the message

b) THE COMMUNICATION SYSTEM SCHEME S = source (emmitter) R = destination (receptor) C = communication channel N = perturbations (noise)

c) TRANSDUCERS = device which changes d) MODEMS = MOdulation / DEModulation e) CODING = translation from one alphabet to another f) THE CHANNEL CAPACITY = bits/seconds (bps,baud)

2.6. INFORMATION TRANSFER IN BIOLOGICAL SYSTEMS a) THE GENETIC CODE: a) THE GENETIC CODE: DNA, 4 bases (A - T / U, C - G) DNA, 4 bases (A - T / U, C - G) REPLICATION, CODONS REPLICATION, CODONS b) CODING IN NERVOUS SYSTEM b) CODING IN NERVOUS SYSTEM - FREQUENCY - ON AXONS - FREQUENCY - ON AXONS - AMPLITUDE - DENDRITES, SYNAPSES - AMPLITUDE - DENDRITES, SYNAPSES c) EXTERNAL INFORMATION - sense organs c) EXTERNAL INFORMATION - sense organs d) INTERNAL INFORMATION - interorceptors d) INTERNAL INFORMATION - interorceptors

3. MEDICAL INFORMATION 3. MEDICAL INFORMATION

3.1. MEDICAL INFORMATION PACIENT – PHYSICIAN RELATIONPACIENT – PHYSICIAN RELATION ELEMENTARY CYCLE OF MEDICAL ACTIVITYELEMENTARY CYCLE OF MEDICAL ACTIVITY MEDICAL INFORMATION USED IN MEDICAL ACTIVITY:MEDICAL INFORMATION USED IN MEDICAL ACTIVITY: –DATA – individual character - facts –KNOWLEDGE – general character - concepts

ELEMENTARY CYCLE OF MEDICAL ACTIVITY

Structural level Studied by: Domain Correspondin g area of MI molecular / sub cellular molecular biology genetics life sciences bioinformatics cell / tissuecell biology organphysiology neuro informatics systembrain theory cognitive sciences body (‘patient’) - paraclinical depts. (investigation) - clinical depts. (diagnosis, treatment) medical sciences medical informatics - community level - public health healthcare healthcare - healthcare activity healthcare managementsciencesinformatics 3.3. CLASIFICAREA INFORMATIEI MEDICALE PE NIVELE STRUCTURALE

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

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. CHAPTERS OF MEDICAL INFORMATICS 4. CHAPTERS OF MEDICAL INFORMATICS I st PART. DATA STORAGE - DATABASES ACQUISITION & PROCESSING: NUMERICAL & QUALITATIVE – BIOSTATISTICS SIGNAL PROCESSING MEDICAL IMAGING II nd PART. MEDICAL KNOWLEDGE MEDICAL DECISION SUPPORT EXTRACTION & FORMALIZATION OF MEDICAL KNOWLEDGE III rd PART. INFORMATION SYSTEMS

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