Unit PHYSICAL SCIENCES

RADIATION PHYSICS

Code	A000082
CFU	2
Teacher	Andrea Orecchini
Teachers	Andrea Orecchini
Hours	24 ore - Andrea Orecchini
Learning activities	Base
Area	Scienze propedeutiche
Academic discipline	FIS/07
Type of study-unit	Obbligatorio (Required)

PHYSICS

Code	50011800
CFU	1
Teacher	Andrea Orecchini
Teachers	Andrea Orecchini
Hours	12 ore - Andrea Orecchini
Learning activities	Base
Area	Scienze propedeutiche
Academic discipline	FIS/07
Type of study-unit	Obbligatorio (Required)

INFORMATICS

Code	GP003730
CFU	2
Teacher	Ivan Gerace
Teachers	Ivan Gerace
Hours	24 ore - Ivan Gerace
Learning activities	Base
Area	Scienze propedeutiche
Academic discipline	INF/01
Type of study-unit	Obbligatorio (Required)
Language of instruction	Italian
Contents	Digital representation of images. Introduction to the C programming language. Management of digital images using C programming language.
Reference texts	Gonzalez, Woods, "Digital Image Processing", Prentice Hall, Pearson Education. Kochan, "Programmare in C. Introduzione al linguaggio", Pearson.
Educational objectives	At the end of the course the student must be able to design and write a simple C language program for the management of digital images.
Prerequisites	No one.
Teaching methods	Frontal lesson. Guided lesson at the computer lab. Problem solving.
Other information	No one.
Learning verification modality	Computer lab test and oral exam.
Extended program	The light. RGB, CMYK, Lab representation. Blur and noise corruption of an image. Punctual, local and global operators for image reconstruction. Quantization problem. Estimation of the optical flow. Separation of components. Tomography. Demosaicing. Variables in C language. Commands for, while and if. File reading and writing. Management of a gray level image. Management and creation of color images.
Obiettivi Agenda 2030 per lo sviluppo sostenibile	4

RESEARCH METHODOLOGY

Code	40285806
CFU	2
Teacher	Donatella Siepi
Teachers	Donatella Siepi
Hours	24 ore - Donatella Siepi
Learning activities	Caratterizzante
Area	Scienze interdisciplinari
Academic discipline	SECS-S/02
Type of study-unit	Obbligatorio (Required)
Language of instruction	Italian
Contents	General information on statistics and its use in medicine. Purposes and methods of statistical analysis, statistical characteristics and classification. DESCRIPTIVE STATISTICS: principles descriptive statistics indexes, their use and their representation Epidemiology and Clinical Trials Probability calculation. INFERENTIAL STATISTICS. Evaluation of data usage and processing. Correlation for the association between qualitative variables. Linear regression. Tables and survival curves.
Reference texts	Fowler J., Jarvis P., Chevannes M.: STATISTICA PER LE PROFESSIONI SANITARIE. Edizioni EdiSES. Availability of teaching materials on the UniStudium platform
Educational objectives	The Statistics module is the only teaching of the CdS statistics and examines the introductory and basic principles necessary for an understanding of the elements of descriptive and inferential statistics. The main objective of the module is to provide students with the knowledge to deal with the management and interpretation of data in the workplace. The main knowledge gained will be: understand and know the main terms of descriptive statistics; know the basics of probability theory; the various aspects of the smooth conduct of clinical trials; how to evaluate the data and their possible processing. The main skills acquired will be organizing, processing, interpreting scientific data produced in the workplace and found in the scientific literature and communicate appropriately the obtained summary information.
Prerequisites	In order to understand and use the concepts described in the teaching it requires knowledge of basic elements of Mathematics, Computer and English.
Teaching methods	Face-to-face lessons: Classroom lessons on all the topics of the module itself with the use of visual media and discussion with the students.
Learning verification modality	The exam includes an oral exam consisting of a discussion aimed at ascertaining the level of knowledge and understanding reached by the student on the topics presented in class and listed in the programs. The student must demonstrate knowledge the notions basic statistics to be able to read and understand an article, evaluate and use data. The oral test will also verify the communication skills of the student, his command of the language, the ability to apply the acquired skills and develop solutions in independent judgment.
Extended program	General information on statistics and its use in medicine. Purposes and methods of statistical analysis, statistical characteristics and classification. DESCRIPTIVE STATISTICS Measurements and sampling in health studies. Data analysis and presentation. Presentation of the results of tables. Main graphic representation (ortogrammi, histograms etc.). absolute frequencies, relative, cumulative. Distribution of frequencies. Measures of central tendency. variability of the measurement. Curves of symmetric and asymmetric frequencies. EPIDEMIOLOGY Frequency measures of disease: prevalence and frequency. Types of studies. Confounding. CLINICAL TRIALS History, nature of clinical trials. types of clinical trials. Ethical aspects. Smooth conduct of a clinical trial. Probability calculation'. Definition and calculation of the probability theory. Event and event space. The measure of probability. basic principles of probability. Bayes theorem and applications. Specificity and sensitivity. positive predictive value, negative predictive values. relative risk and odds-ratio. ROC-curves and their interpretation. empirical law of the case. Theoretical probability distributions: Gaussian and binomial and Poisson. Applications. INFERENTIAL STATISTICS. Outline of the central limit theorems. standard error. Levels of significance. Confidence intervals. standard normal distribution and T-student distribution. Testing hypotheses: the concept of hypothesis, error of first kind and II species. power of the test. Tests based on a sample. Z test for the mean. One-tailed test and two-tailed. Comparing averages for paired and independent samples. Parametric and non-parametric statistics. Analysis of variance. How to use the t-test to identify differences between groups. Test for multiple comparisons. Test ¿2: meaning, properties and applications. Correlation for the association between qualitative variables, Pearson coefficient, Spearman coefficient. Linear regression. Tables and survival curves.