Unit MEDICAL AND SCIENTIFIC METHODOLOGY II
- Course
- Medicine and surgery
- Study-unit Code
- GP005549
- Curriculum
- In all curricula
- CFU
- 7
- Course Regulation
- Coorte 2023
- Offered
- 2024/25
- Type of study-unit
- Obbligatorio (Required)
- Type of learning activities
- Attività formativa integrata
BIOINGEGNERIA ED INFORMATICA MEDICA
| Code | GP005612 |
|---|---|
| CFU | 2 |
| Learning activities | Affine/integrativa |
| Area | Attività formative affini o integrative |
| Academic discipline | ING-INF/06 |
| Type of study-unit | Obbligatorio (Required) |
Cognomi A-L
- CFU
- 2
- Teacher
- Paolo Valigi
- Teachers
- Paolo Valigi
- Hours
- 25 ore - Paolo Valigi
- Language of instruction
- Italian
- Contents
- Introduction to health informatics and bioengineering, with discussion on classic and innovative applications.
- Reference texts
- Material from the instructor and scientific papers.
Selected pages from “Health Informatics: Practical Guide For Healthcare And Information Technology Professionals (Seventh Edition)” Robert E Hoyt - Educational objectives
- To understand basic concept of medical computer science and bioengineering, their limits and areas of application.
- Prerequisites
- None.
- Teaching methods
- Frontal lessons and discussions.
- Other information
- During the classes also detailed discussions on selected topics will be given.
- Learning verification modality
- Mode of conducting the examination: Written test with 34 closed-ended questions and one open-ended question devoted to the presentation of a medical procedure, simplified, in the form of an algorithm.
Two intermediate tests are scheduled during the course of the lectures, with closed-answer questions only, which can replace the examination in the case of an average grade in the two tests higher than 18/30.
The module grade is assessed as 32/30; honors are awarded with 32/30, grades below 32/30 and up to 30/30 correspond to 30/30, grades below 30/30 correspond to the final grade. In case of rounding (e.g., in midterm tests) the nearest whole number is chosen.
Verification of clinical skills: Not provided in the module.
Verification of skills acquired during internship: Not provided in the module.
Method of awarding final grade: Arithmetic mean of the marks achieved in the individual disciplines, rounded up (30L=31) - Extended program
- Course introduction and motivation.
Classical and innovative applications.
Basic on Artificial Intelligence applications to Medicine, and ethical implications.
Information, binary code, and disease classification. Algorithms and medical applications.
Health information systems.
Signals, frequency analysis.
Systems and responses. Medical examples.
Compartment models and medical applications and examples. - Obiettivi Agenda 2030 per lo sviluppo sostenibile
- Salute e benessere
Cognomi M-Z
- CFU
- 2
- Teacher
- Elisabetta Zanetti
- Teachers
- Elisabetta Zanetti
- Hours
- 25 ore - Elisabetta Zanetti
- Language of instruction
- Italian
- Contents
- Health informatics and main concepts concerning medical instrumentation
- Reference texts
- - Slides and notes available on Unistudium
- Webster JG "Medical Instrumentation: Application and Design, 4th Edition"
- Bemmel, J.van “Handbook of Medical Informatics”
- Robert E Hoyt “Health Informatics: Practical Guide For Healthcare And Information Technology Professionals (Fifth Edition)” - Educational objectives
- The student will achieve the following results:
• Ability to understand the performance of different sensors and data acquisition systems to make a reasoned choice.
• Awareness of the main techniques of signal analysis in the time domain and frequency.
• Capacity for critical analysis of the images.
• Awareness of electrical hazards and precautions to minimize them.
• being able to interact with the technology of ICT in the medical field,
• knowledge of coding tools in general and in the medical field in particular,
• Knowledge of main components of computers
• Internet and its protocols
• knowledge of databases and how to interact with these
• Main health information systems and their peculiarities
• Telemedicine - Prerequisites
- Maths and Physics from secondary school
- Teaching methods
- Lectures with the use of slides (this material is uploaded on UNISTUDIUM for all registered students.
Practical lessons to the computer.
"Flipped classroom" approach for pratical applications. - Other information
- The students can require further information by emails
- Learning verification modality
- Written 1h test, made of two parts: Bioengineering and Medical Informatics- 10 questions with short answers.
The final score will be computed form the airthmetic average of the score obtaines in Medical statistics and Bioengineering, rounded up (30L=31) - Extended program
- Bioengineering
• Sensors (4h)
o Sensor specifications: accuracy, precision, bias, repeatability, linearity, range, sensitivity, hysteresis, temperature drift.
o Calibrating a sensor
o Meaning of the impedance in the input and output of a sensor
• Signals and their treatment (4h)
o Frequency analysis: utility, possible errors
o Dynamic systems response
o Analog / digital converters
o Sampling a signal, Nyquist theorem, antialiasing filters
o Amplifiers
o Filters
o Disturbances in the transmission of signals
o Images and Bioimaging: resolution and depth, encryption, compression techniques
o Specifications of a display
o Editing an image: value processing of color or luminance; morphological operations
o CT: operating principle
• Risk factors in hospital (2h)
o Classification of medical equipment according to risk classes
o Electrical Hazard: Zone 'Patient', Effects of electricity (microshock, macroshock)
o Classification of medical locations rooms.
o Usefulness of 'grounded', earth contact, isolation transformer.
o Equipment type B, BF, CF
Medical Informatics
• Information and Medical Coding (2 h)
o Alphabet and semantics
o Numerical, textual, Boolean information and respective coding
o Algorithms (reference structures: sequence, iteration, selection )
o Data structures (vectors, records, trees, graphs)
• Classification in medicine (2 h)
o Classification of diseases (ICD)
o DRG: meaning, assessment, indices of Performance and case-mix
o Electronic health record: SNOMED
• Computer architecture and how it works (2 h)
o Main components: bus, memoria (RAM, cache, mass storage), CPU, I/O devices and respective classifications
o Operative systems
o File System
• Computer networks: (2 h)
o Server, Host, web link
o Protocols (http, IMAP, POP3, SMTP)
o IP address: static or dynamic
o State of the art in health informatics: RIS, PACS, DICOM standard and electronic health record (FSE)
o Telemedicine
NURSING
| Code | GP005614 |
|---|---|
| CFU | 1 |
| Learning activities | Affine/integrativa |
| Area | Attività formative affini o integrative |
| Academic discipline | MED/45 |
| Type of study-unit | Obbligatorio (Required) |
Cognomi A-L
- CFU
- 1
- Teacher
- Mirella Giontella
- Teachers
- Mirella Giontella
- Hours
- 12.5 ore - Mirella Giontella
Cognomi M-Z
- CFU
- 1
- Teacher
- Mirella Giontella
- Teachers
- Mirella Giontella
- Hours
- 12.5 ore - Mirella Giontella
MEDICAL STATISTICS
| Code | GP005613 |
|---|---|
| CFU | 3 |
| Learning activities | Caratterizzante |
| Area | Inglese scientifico e abilità linguistiche, informatiche e relazionali, pedagogia medica, tecnologie avanzate e a distanza di informazione e comunicazione |
| Academic discipline | MED/01 |
| Type of study-unit | Obbligatorio (Required) |
Cognomi A-L
- CFU
- 3
- Teacher
- Fabrizio Stracci
- Teachers
- Fabrizio Stracci
- Hours
- 37.5 ore - Fabrizio Stracci
- Language of instruction
- Italian
- Contents
- The basis of scientific investigation
The role of statistic methods in biomedical research
Descriptive statistics
Inferential statistics
Regression models to analyze relationships among variables - Reference texts
- Primer of biostatistics by Stanton A. Glantz
or
Principles of Biostatistics by Marcello Pagano, Kimberlee Gauvreau - Educational objectives
- Basic data analysis
Understanding of the role of statistics in medicine
Critical reading of methods and results in published biomedical research - Prerequisites
- none
- Teaching methods
- Lesson
Practical exercises - Other information
- Learning verification modality
- Oral exam. Duration about 15-20 minutes based on two questions. A question will be devoted to explore knowledge of common statistics, the concept of statistical testing and regression models. Another question will investigate competence in the application of simple statistical techniques and critical reading of methods applied in epidemiologic and clinical research. Final grade will be obtained as the arithmetic mean of results of integrated courses.
- Extended program
- 1.1 Statistics definitions and scope
1.2 Statistical methods in medical research
2. Data
2.1 Types of variables
2.2 Tabulation and processing of data
2.3 Diagrams
2.4 Descriptive statistics
2.5 Measures of central tendency
2.6 Measures of variability
3. Probability
3.1 Frequentist definition of probability
3.2 Probability distributions
3.3 The normal or Gaussian distribution
3.4 Probability distributions and applications
4. Populations and samples
4.1 Parameters and their estimation
4.2 Sampling
5. Statistical inference
5.1 Point and interval estimation
5.2 Confidence interval for the sample mean
5.3 Significance testing
5.4 Parametric Hypothesis Tests: Student’s t test and Analysis of Variance
5.5 Confidence interval for the difference between two means
5.6 Non-Parametric Hypothesis Tests: chi-squared test
6. Regression and correlation
6.1 Regression models
6.2 Linear regression
6.2.1 Linear regression equation: parameters estimation using the ordinary least squares method
6.2.2 Tests of significance in regression
6.2.3 Confidence interval for the linear regression coefficient b
6.3 Correlation
6.4 Critical reading of results from multivariable regression models
6.5 Multivariable modeling, an introduction - Obiettivi Agenda 2030 per lo sviluppo sostenibile
Cognomi M-Z
- CFU
- 3
- Teacher
- Fabrizio Stracci
- Teachers
- Fabrizio Stracci
- Hours
- 37.5 ore - Fabrizio Stracci
- Language of instruction
- Italian
- Contents
- The basis of scientific investigation
The role of statistic methods in biomedical research
Descriptive statistics
Inferential statistics
Regression models to analyze relationships among variables - Reference texts
- Primer of biostatistics by Stanton A. Glantz
or
Principles of Biostatistics by Marcello Pagano, Kimberlee Gauvreau - Educational objectives
- Basic data analysis
Understanding of the role of statistics in medicine
Critical reading of methods and results in published biomedical research - Prerequisites
- none
- Teaching methods
- Lesson
Practical exercises - Other information
- Learning verification modality
- Oral exam. Duration about 15-20 minutes based on two questions. A question will be devoted to explore knowledge of common statistics, the concept of statistical testing and regression models. Another question will investigate competence in the application of simple statistical techniques and critical reading of methods applied in epidemiologic and clinical research. Final grade will be obtained as the arithmetic mean of results of integrated courses.
- Extended program
- 1.1 Statistics definitions and scope
1.2 Statistical methods in medical research
2. Data
2.1 Types of variables
2.2 Tabulation and processing of data
2.3 Diagrams
2.4 Descriptive statistics
2.5 Measures of central tendency
2.6 Measures of variability
3. Probability
3.1 Frequentist definition of probability
3.2 Probability distributions
3.3 The normal or Gaussian distribution
3.4 Probability distributions and applications
4. Populations and samples
4.1 Parameters and their estimation
4.2 Sampling
5. Statistical inference
5.1 Point and interval estimation
5.2 Confidence interval for the sample mean
5.3 Significance testing
5.4 Parametric Hypothesis Tests: Student’s t test and Analysis of Variance
5.5 Confidence interval for the difference between two means
5.6 Non-Parametric Hypothesis Tests: chi-squared test
6. Regression and correlation
6.1 Regression models
6.2 Linear regression
6.2.1 Linear regression equation: parameters estimation using the ordinary least squares method
6.2.2 Tests of significance in regression
6.2.3 Confidence interval for the linear regression coefficient b
6.3 Correlation
6.4 Critical reading of results from multivariable regression models
6.5 Multivariable modeling, an introduction - Obiettivi Agenda 2030 per lo sviluppo sostenibile
PROFESSIONALISING TRAINING IN NURSING
| Code | GP005615 |
|---|---|
| CFU | 1 |
| Learning activities | Altro |
| Area | Tirocini formativi e di orientamento |
| Academic discipline | MED/45 |
| Type of study-unit | Obbligatorio (Required) |
Cognomi A-L
- CFU
- 1
- Teacher
- Mirella Giontella
- Teachers
- Mirella Giontella
- Hours
- 25 ore - Mirella Giontella
Cognomi M-Z
- CFU
- 1
- Teacher
- Mirella Giontella
- Teachers
- Mirella Giontella
- Hours
- 25 ore - Mirella Giontella