Scientific programming for medical data analysis

Course Information
TitleΜαθηματικές και προγραμματιστικές τεχνικές ανάλυσης ιατρικών δεδομένων / Scientific programming for medical data analysis
CodeΙΠΑ005
Interdepartmental ProgrammeIPPS "Medical Informatics" (2019-today)
Collaborating SchoolsMedicine
Informatics
Electrical and Computer Engineering
Cycle / Level2nd / Postgraduate
Teaching PeriodWinter
CoordinatorIoanna Chouvarda
CommonNo
StatusActive
Course ID600016649

Programme of Study: IPPS "Medical Informatics" (2019-today)

Registered students: 11
OrientationAttendance TypeSemesterYearECTS
KORMOSCompulsory Course117.5

Class Information
Academic Year2020 – 2021
Class PeriodWinter
Faculty Instructors
Instructors from Other Categories
Weekly Hours2
Class ID
600176755
Course Type 2011-2015
Specific Foundation / Core
Mode of Delivery
  • Face to face
Erasmus
The course is also offered to exchange programme students.
Prerequisites
General Prerequisites
Basic knowledge of computer systems Basic understanding of programming Familiarisation with English Language
Learning Outcomes
The purpose of the lesson is * to provide students with the necessary skills to understand data analysis issues in health * to demonstrate necessary basic techniques * to set a framework of modern methods and techniques * to make student students discuss / contemplate on modern problems of analysis and design of health methods  Objectives of the course. At the end of the course the students will be able to: * Use appropriate methodologies for medical data analysis * Have the necessary initial familiarisation with the various tools currently used worldwide * Be able to make appropriate use of techniques and tools to develop (at least) data analysis systems for medical applications * Discuss requirements for different analysis & design approaches
General Competences
  • Apply knowledge in practice
  • Retrieve, analyse and synthesise data and information, with the use of necessary technologies
  • Work autonomously
  • Work in teams
  • Work in an interdisciplinary team
Course Content (Syllabus)
Thematic areas, supported by lectures, workshops and works --- High level scripting and prototyping --- scientific applications in Matlab --- analysis and visualization of medical data in R / web interactive applications --- data management and data structures, computational Python performance --- seminar lessons, machine learning, high performance programming, linux environment
Educational Material Types
  • Notes
  • Slide presentations
  • Video lectures
  • Book
Use of Information and Communication Technologies
Use of ICT
  • Use of ICT in Course Teaching
  • Use of ICT in Laboratory Teaching
  • Use of ICT in Communication with Students
  • Use of ICT in Student Assessment
Description
Computing is at the core of this lesson
Course Organization
ActivitiesWorkloadECTSIndividualTeamworkErasmus
Lectures521.7
Laboratory Work100.3
Reading Assigment602
Project682.3
Written assigments351.2
Total2257.5
Student Assessment
Description
The evaluation is based on a set of individual and group work (on each thematic area) that are completed and examined during the semester.
Student Assessment methods
  • Written Exam with Multiple Choice Questions (Summative)
  • Written Assignment (Summative)
  • Performance / Staging (Formative)
  • Labortatory Assignment (Formative)
Bibliography
Additional bibliography for study
ηλεκτρονικό υλικό που αφορά τις επιμέρους τεχνολογίες που διδάσκονται στις θεματικές περιοχές
Last Update
09-11-2018