Methods of experimental and technological research

A.Y. 2019/2020
5
Max ECTS
50
Overall hours
SSD
FIS/07 ING-INF/05 MED/36 SECS-S/02
Language
Italian
Learning objectives
- know and interpret the role of variability in biomedical research
- know how to apply and interpret basic statistical methods
- apply the necessary methodology to assess the accuracy and precision of the data
- know the quantitative approaches
- interpret quantitative results
Expected learning outcomes
At the end of the course the student must be able to know how to apply the acquired knowledge to read critically the results of scientific studies.
Course syllabus and organization

Single session

Responsible
Prerequisites for admission
No prior knowledge required.
Assessment methods and Criteria
Written exam with 30 quizzes (with 3 or 4 answer options). Each exact answer will be assigned 1 point. There are no penalties for unanswered or incorrect answers. The test can also be taken twice in the same session.
The final exam aims to assess the achievement of the set educational objectives.
The booking on the UNIMIA portal, within the dates established for each appeal, is mandatory for the examination.
Sistema di elaborazione delle informazioni per controllo di qualità nelle applicazioni biomediche
Course syllabus
Using Excel for basic statistics.
Statistics program R.
Statistics application with R.
Definition of quality.
Quality management.
Legislation related to quality controls.
Statistical methods for quality control.
Use of clinical G2.
Teaching methods
The course is divided into a series of lectures with slide shows in Power Point. The lectures slides are uploaded to the Ariel website.
Teaching Resources
POLI: Excel 2016. Formule e analisi dei dati - Hoepli editore, ISBN-13: 978-8820375102
Elaborazione delle informazioni e reti di calcolatori
Course syllabus
Computer network services.
Network classification.
General structure of network architectures, introduction to protocols.
The transmission media.
Local networks.
Network level: routing and IP protocol.
Transport level: TCP and UDP.
Level of TCP / IP applications.
Microsoft protocols.
Teaching methods
The course is divided into a series of lectures with slide shows in Power Point. The lectures slides are uploaded to the Ariel website.
Teaching Resources
GERACE: La logica dei sistemi di elaborazione - Editori Riuniti (University Press)
Ricerca in radiologia medica
Course syllabus
1. Evidence-Based Medicine.
1.1. Hierarchy of studies on diagnostic tests.
2. Diagnostic performance measures.
2.1. The results of a survey compared to a standard reference.
2.2. Sensitivity and specificity.
2.3. Predictive values, diagnostic accuracy and influence of disease prevalence.
2.4. Bayes theorem or subjective probability or conditional probability and likelihood ratio.
2.5. Discriminant thresholds and ROC curves.
3. Overdiagnosis.
4. Study design, systematic reviews and levels of evidence.
4.1. Phases 1, 2, 3 and 4 of the pharmacological research.
4.2. Classification of studies.
4.3. Experimental studies and control group.
4.4. Randomized trials.
4.4. Observational studies.
4.5. Sample size.
4.6. Systematic reviews (metanalysis).
4.7. Levels of evidence.
5. How to write a scientific radiological work.
5.1. Are informed consent and approval by the Ethics Committee always necessary?
5.2. Title, running title and Title page.
5.3. The four-section diagram, their dimensions and the editing sequence.
5.4. "Introduction": why did you do it?
5.5. "Materials and methods": what did you do and how did you do it?
5.6. «Results»: what did you find?
5.7. "Discussion": what is the meaning of your results?
5.8. "References."
5.9. «Abstract» and «Key words».
Teaching methods
The course is divided into a series of lectures with slide shows in Power Point. The lectures slides are uploaded to the Ariel website.
Teaching Resources
SARDANELLI, DI LEO: Biostatistics for radiologists - Springer, 2009
SARDANELLI, DI LEO: Biostatistica in radiologia - Springer, 2009
Statistica per la ricerca sperimentale e tecnologica
Course syllabus
1. Variables and measurement scales, normal distribution and confidence intervals.
1.1. Variables and measurement scales.
1.1.1. Categorical variables.
1.1.2. Discrete numerical variables.
1.1.3. Continuous numeric variables.
1.2. Measurement scales.
1.3. The Gauss distribution.
1.4. Notes on descriptive statistics.
1.5. Indices of central tendency.
1.6. Dispersion around the central tendency: variance and standard deviation.
1.7. Standard error of the average.
1.8. The confidence intervals.
2. Null hypothesis, significance and statistical power.
2.1. Hypothesis null and principle of falsifiability.
2.2. Significance threshold, type I error and type II error.
2.3. Statistical power.
2.4. Why 0.05?
2.5. Interpreting the p.
3. Parametric and non-parametric statistics.
3.1. Parametric statistics.
3.1.1. The basics of parametric statistics.
3.1.2 Comparison between two sample averages: Student's t test.
3.1.3 Comparison of three or more sample averages: the analysis of variance.
3.1.4. ANOVA for independent and dependent groups.
3.1.5 The parametric statistics in radiology.
3.2. Non-parametric statistics.
3.2.1 A sample with two dependent or coupled measurements.
3.2.2. Variables measured on a dichotomous scale.
3.2.3. Variables measured on ordinal scale.
3.2.4. Variables measured on an interval or rational scale.
3.2.5 Two independent samples.
3.2.6. Variables measured on nominal or ordinal scale.
3.2.7. Variables measured on an interval or rational scale.
3.2.8. Three or more (k) dependent samples.
3.2.9. Variables measured on a dichotomous scale.
3.2.10. Variables measured on ordinal, interval or rational scale.
3.2.11 Three or more (k) independent samples.
3.2.12. Data measured on nominal or ordinal scale.
3.2.13. Variables measured on an interval or rational scale.
3.2.14. Considerations on non-parametric tests.
4. Correlation and linear regression.
4.1. Association and causation.
4.2. Correlation between continuous variables.
4.3. Interpretation of the correlation coefficient.
4.4. Significance test.
4.5. Rank correlation.
4.6. Linear regression.
4.6.1. The calculation of the coefficients.
4.7. Interpretation of the regression line.
4.8. Limitations on the use of linear regression.
5. Reproducibility: intraobserver and interobserver variability.
5.1. Sources of variability.
5.2. Why is it important to know the variability of the measurements?
5.3. The intra- and interobserver variability for continuous variables. The Bland-Altman method.
5.4. Interpretation of the results of the Bland-Altman method.
5.5. Intra- and interobserver variability for categorical variables: Cohen's kappa.
Teaching methods
The course is divided into a series of lectures with slide shows in Power Point. The lectures slides are uploaded to the Ariel website.
Teaching Resources
SARDANELLI, DI LEO: Biostatistics for radiologists - Springer, 2009
SARDANELLI, DI LEO: Biostatistica in radiologia - Springer, 2009
Elaborazione delle informazioni e reti di calcolatori
ING-INF/05 - INFORMATION PROCESSING SYSTEMS - University credits: 2
Lessons: 20 hours
Professor: Dupplicato Andrea
Ricerca in radiologia medica
MED/36 - IMAGING AND RADIOTHERAPY - University credits: 1
Lessons: 10 hours
Sistema di elaborazione delle informazioni per controllo di qualità nelle applicazioni biomediche
FIS/07 - APPLIED PHYSICS - University credits: 1
Lessons: 10 hours
Professor: De Marco Paolo
Statistica per la ricerca sperimentale e tecnologica
SECS-S/02 - STATISTICS FOR EXPERIMENTAL AND TECHNOLOGICAL RESEARCH - University credits: 1
Lessons: 10 hours
Professor(s)
Reception:
To be defined after emailing to francesco.sardanelli@unimi.it
Dept. of Radiology, IRCCS Policlinico San Donato, Via Morandi 30, 20097 San Donato Milanese, Milan, Italy