• HOME
• ABOUT US
  • Name Address
  • General Description
  • Governance
  • Academic Calendar
  • Degree Programmes
  • List of Programmes in English
  • General Admission and Registration Procedures
  • Credit Mobility and Recognition of Prior Learning
  • ECTS Credit Allocation
  • Academic Guidance
  • Contacts
• Degree Programmes
  • Third Cycle Programmes (Doctorate Degree)
  • Second Cycle Programmes (Master's Degree)
  • First Cycle Programmes (Bachelor's Degree)
  • Short Cycle Programmes (Associate's Degree)
• GENERAL INFORMATION FOR STUDENTS
  • Cost of Living
  • Accommodation
  • Meals
  • Medical Facilities
  • Facilities for Disabled Students
  • Insurance
  • Financial Supports
  • Student Affairs Office
  • Practical Information for International Students
  • Language Courses
  • Work Placement Possibilities
  • Sports, Social and Cultural Facilities
  • Student Associations and Clubs
  • About İzmir - Turkey
• INTERNATIONAL RELATIONS
  • International Relations Office
  • Registration Procedures
  • Agreements
  • Coordinators
  • Documents
  • List of Programmes in English
  • ECTS / DS Labels

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS BMT 5013 BIOMEDICAL COMPUTING ELECTIVE 2 2 0 8

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

PROFESSOR DOCTOR MUSTAFA ALPER SELVER

Offered to

Industrial Ph.D. Program In Advanced Biomedical Technologies Industrial Ph.D. Program In Advanced Biomedical Technologies Biomedical Tehnologies (English)

Course Objective

Understanding basic principles of biomedical computing by practicing the time domain, frequency domain techniques, filtering both domains, ROC analysis, basic statistical learning techniques and their biomedical applications.

Learning Outcomes of the Course Unit

1   Gaining knowledge on biomedical signals 2   Gaining knowledge on 1-D, 2-D convolution and filtering of biomedical signals 3   Gaining knowledge on basic statistical learning, ROC analysis and applications on biomedical research

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 Review of Linear Algebra and introduction to Matlab 2 Convolution integral and implementation 3 1-D filtering of biomedical signals 4 2-D filtering of biomedical images 5 Frequency and Time Domain concepts, Fourier Transform 6 1-D/2-D filtering in frequency domain 7 Midterm I 8 Basic principles and algorithms of statistical learning 9 Implementation of perceptron algorithms 10 ROC analysis and implementation 11 Usage of statistical learning for biomedical applications 12 Midterm II 13 Applications of Biomedical Computing 14 Final

Recomended or Required Reading

To be announced.

Planned Learning Activities and Teaching Methods

1 midterm+1 final+homeworks

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA 1 ASG ASSIGNMENT 2 PRS PRESENTATION 3 FCG FINAL COURSE GRADE ASG * 0.50 + PRS * 0.50 *** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

To be announced.

Language of Instruction

English

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

alper.selver@deu.edu.tr

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours) Lectures 14 2 28 Preparations before/after weekly lectures 14 4 56 Preparation for midterm exam 2 15 30 Preparation for final exam 1 20 20 Preparing assignments 5 10 50 Midterm 2 3 6 Final 1 3 3 TOTAL WORKLOAD (hours) 193

Contribution of Learning Outcomes to Programme Outcomes

PO/LO PO.1 PO.2 PO.3 PO.4 PO.5 PO.6 PO.7 PO.8 PO.9 PO.10 LO.1 5 4 5 3 4 2 2 LO.2 5 5 5 2 4 3 2 LO.3 5 4 5 4 3 4 2