Dr. İnci M. Baytaş will give a seminar on “Data-Driven Techniques in Biomedical Informatics” on November 27 at 4 pm. The abstract of the talk and a short bio is shared below.

Bio:
İnci M. Baytaş received her bachelor's and master's degrees from Electronics and Communication Engineering Department at Istanbul Technical University in 2012 and 2014, respectively. She joined the Ph.D. program of Computer Science and Engineering at Michigan State University in 2014. She has been working as an Assistant Professor in the Computer Engineering Department at Bogazici University since 2019. Her research interests are deep learning, adversarial machine learning, multi-task learning, temporal analysis, and their applications on biomedical informatics.

Abstract:
With innovations in digital data acquisition devices and increased memory capacity, virtually all commercial and scientific domains have been witnessing exponential growth in the amount of data they can collect. For instance, healthcare is experiencing tremendous growth in digital patient information due to the high adaptation rate of electronic health record systems in hospitals. The abundance of data offers many opportunities to develop robust and versatile algorithms. Biomedical informatics is an interdisciplinary domain, where machine learning techniques are adopted to analyze electronic health records (EHRs). EHR comprises digital patient data with various modalities and depicts an instance of big data. For this reason, analysis of digital patient data is quite challenging although it provides a rich source for clinical research. In this seminar, common tasks and challenges in biomedical informatics will be introduced. Then, state-of-the-art machine learning and deep learning solutions to some of the prevalent biomedical informatics tasks will be presented.