Opportunities and Challenges for Clinical Practice in Detecting Depression Using EEG and Machine Learning
Published by
Sensors
Summary
journal-article
About
Eda Kalafatić is a researcher at the Faculty of Electrical Engineering and Computing, University of Zagreb where she also received the M.Sc. degree in electronic and computer engineering. Her current research interests include signal processing, biomedical engineering and machine learning with applications.
Work
Faculty of Electrical Engineering and Computing in Zagreb
|Assistant
Croatia
→
Faculty of Electrical Engineering and Computing in Zagreb
|Researcher
Croatia
→
Education
Sveučilište u Zagrebu Fakultet elektrotehnike i računarstva
Croatia
→
mag. ing. el. techn. inf.
Sveučilište u Zagrebu Fakultet elektrotehnike i računarstva
Croatia
→
univ. bacc. ing. el. techn. inf.
Publications
Impact of EEG Signal Preprocessing Methods on Machine Learning Models for Affective Disorders
Published by
2024 47th MIPRO ICT and Electronics Convention (MIPRO)
Summary
conference-paper
Publicly Available Datasets for Predictive Maintenance in the Energy Sector: A Review
Published by
IEEE Access
Summary
journal-article
Publicly Available Datasets for Predictive Maintenance in the Energy Sector: A Review
Published by
IEEE Access
Summary
journal-article
Borderline and Depression: A Thin EEG Line
Published by
Clinical EEG and Neuroscience
Summary
journal-article
Borderline and Depression: A Thin EEG Line
Published by
Clinical EEG and Neuroscience
Summary
journal-article