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SETSCI - Volume 6(1) (2023)
BMYZ2023 - Cognitive Models and Artificial Intelligence Conference, Ankara, Türkiye, Oct 26, 2023

Assessment of Undergraduate Student Graduation Projects Focusing on Deep Learning in Biomedical Sciences
Uğur Baysal1*
1Hacettepe University, Ankara, Türkiye
* Corresponding author: ubaysal@ee.hacettepe.edu.tr
Published Date: 2023-11-26   |   Page (s): 64-69   |    62     2
https://doi.org/10.36287/setsci.6.1.025
ABSTRACT Biomedical Sciences are the technological disciplines that aim to explore methods to obtain, produce, reveal or produce information related to understand, model, monitor, diagnose, combat problems in human and/or animal bodies. Machine learning in biomedical technology is relatively new field of scientific research area and engineering technology application field, its growing rate is so fast that it is put into lower education levels than graduate level. In this work, educational contributions of senior year electrical and electronics engineering student projects will be discussed. After supervising four undergraduate student graduation projects, done by total of six students, it is concluded that the undergraduate electrical and electronics engineering average student is ready to apply deep learning techniques to biomedical sciences with restricted budget conditions, internet resources, available computational infrastructure and credit-hour load from the other courses leading graduation. Moreover, a student is already aware of and is ready to fully consider his professional work obligations health, safety, manufacturability, sustainability, economy direct or indirect effects to society, ethics, and environment.
KEYWORDS Biomeical Engineering, Deep Learning, Artificial Intelligence, ECG, ACS, Biology
REFERENCES T.A. Bozkurtlar, E. Kaya, Application of Deep Learning Algorithms to Classify Electrocardiography (ECG) Signals obtained from Acute Coronary Syndrome (ACS), Hacettepe University Dept. Electrical and Electronics Engineering, ELE402 Graduation Project II Course Final Report, 22.01.2023.

B.Aldemir, İ.Aksoy, Processing and Classification of Microscope Images, Hacettepe University Dept. Electrical and Electronics Engineering, ELE402 Graduation Project II Course Final Report, 02.09.2023.

F.K.Terzi, Implementation of medical decision support software library for classifying heart bioelectric signals,. Hacettepe University Dept. Electrical and Electronics Engineering, ELE402 Graduation Project II Course Final Report, 03.09.2023.

F.Ramiz, .Development of Convolutional Neural Network for ECG Beat Classification to Detect and Categorize Myocardial Infarction, Hacettepe University Dept. Electrical and Electronics Engineering, ELE402 Graduation Project II Course Final Report ,12.01.2023.

Shubham Mittal & Yasha Hasija, Applications of Deep Learning in Healthcare and Biomedicine chapter in "Deep Learning Techniques for Biomedical and Health Informatics” (Part of the Studies in Big Data book series (SBD,volume 68), 15 November 2019.

F Jiang, Y Jiang, H Zhi, Y Dong, H Li, S Ma, Y Wang, Q Dong, H Shen, Y Wang, Artificial intelligence in healthcare: past, present and future, Stroke and vascular neurology, 2017.


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