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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS EEE 5076 BIOMEDICAL SIGNAL PROCESSING ELECTIVE 3 0 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 MEHMET KUNTALP

Offered to

Ph.D. in Biotechnology Industrial Ph.D. Program In Advanced Biomedical Technologies Industrial Ph.D. Program In Advanced Biomedical Technologies ELECTRICAL AND ELECTRONICS ENGINEERING (ENGLISH) Biomedical Tehnologies (English) ELECTRICAL AND ELECTRONICS ENGINEERING (ENGLISH) Ph.D. in Biotechnology ELECTRICAL AND ELECTRONICS ENGINEERING (ENGLISH) BIOTECHNOLOGY

Course Objective

The course aims to provide the students with a detailed knowledge on machine learning techniques for disease diagnosis from biomedical signals.

Learning Outcomes of the Course Unit

1   Learn different kinds of biomedical signals. 2   Understand how the preprocessing of these signals is done 3   Learn the basics of machine learning 4   Learn feature engineering 5   Gain experience on scientific research paper writing

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 Biomedical Signals, Databases and Open Sources 2 Data Acquisition Concepts 3 Denoising 4 Data Preparation 5 Machine Learning Basics 6 Feature Extraction 7 Postprocessing of Features 8 Feature Selection 9 Classification 10 Clustering 11 Anomaly Detection 12 Midterm 13 Research Paper Study 14 Research Paper Study

Recomended or Required Reading

to be announced

Planned Learning Activities and Teaching Methods

Research Homework Presentation Report

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA 1 MTE MIDTERM EXAM 2 CME COMMENTS 3 RAS RESEARCH ASSIGNMENT 4 FCG FINAL COURSE GRADE MTE * 0.20 + CME * 0.10 + RAS * 0.70

Further Notes About Assessment Methods

None

Assessment Criteria

Homework, Midterm, and Term Project

Language of Instruction

English

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

mehmet.kuntalp@deu.edu.tr

Office Hours

will be posted

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours) Lectures 14 3 42 Independant Study 11 6 66 Project Preparation 1 80 80 Midterm 1 3 3 TOTAL WORKLOAD (hours) 191

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 4 3 LO.2 4 3 3 2 5 LO.3 5 5 5 5 5 5 5 5 5 5 LO.4 5 5 5 5 5 5 5 5 5 5 LO.5 5 5 5 5 5 5 5 5 5 5