Unit DATA SCIENCE FOR HEALTH SYSTEMS
- Course
- Computer engineering and robotics
- Study-unit Code
- 70A00039
- Curriculum
- Data science
- Teacher
- Alessio De Angelis
- Teachers
-
- Alessio De Angelis
- Hours
- 48 ore - Alessio De Angelis
- CFU
- 6
- Course Regulation
- Coorte 2021
- Offered
- 2022/23
- Learning activities
- Affine/integrativa
- Area
- Attività formative affini o integrative
- Academic discipline
- ING-INF/07
- Type of study-unit
- Obbligatorio (Required)
- Type of learning activities
- Attività formativa monodisciplinare
- Language of instruction
- Italian
- Contents
- The goal of the course is to provide tools for addressing data science problems in the biomedical field.
The first part of the course deals with the origin of data, with the study of measurement theory and the main classes of biomedical measurements. Particular focus is given to bioimages.
The second part of the course is dedicated to the fundamental statistical techniques relevant for the biomedical field.
To develop practical skills, an important portion of the course is comprised of computer exercises using software tools that are widely applied for statistical analysis of biomedical data.
The main concepts are presented through the use of example datasets. - Reference texts
- Course material provided by the instructor.
- Educational objectives
- - understand the basis of statistical and measurement methods used in the biomedical field
- understand the main problems in some of the application areas of biomedical data science
- develop skills in using the main software tools used in biomedical data science
- acquire the terminology of this sector - Prerequisites
- Probability theory
- Teaching methods
- Classroom lectures. Computer exercises.
- Other information
- Lecturer: alessio.deangelis@unipg.it
- Learning verification modality
- - written exam comprised of multiple-choice questions and open questions
- project work, survey or experimental type, performed by 1 to 4 people. Brief report and presentation
- Optional oral test - Extended program
- 1. Origin of data: measurement
- Measurement theory and uncertainty
- Biomedical measurement
- Bioimages
2. Biostatistics:
- Statistical studies
- Hypotesis test, inference in the biomedical field
3. Data science applications in the biomedical field
Exercises using the R language in the RStudio environment