Type of studies | Title |
---|---|
Doctoral Academic Studies | Biomedical Engineering (Year: 1, Semester: Winter) |
Category | Scientific-professional |
Scientific or art field | Biomedicinsko inženjerstvo |
ECTS | 10 |
The objective of the course is to enable students to actively study the scientific literature and participate in the study research work in the field of machine learning in medicine and healthcare.
The student is able to actively study the scientific literature and conduct the study research work in the field of machine learning in medicine and healthcare.
Linear and quadratic classification, Non-parametric (distribution free) classification, Overfitting and cross validation, Feature Extraction and Selection, Cluster analysis, Deep learning Algorithms. A part of the course work is conducted through independent individual study and research work in the field of Nonlinear Control Systems. The research study work requires the student`s active and constant interest in and reading of the primary scientific resources, the organisation and conducting of experiments, numerical simulations and, optionally, writing a paper in the field of machine learning in medicine and healthcare.
Lectures, seminar paper, tutorial work. Research study work.
Authors | Title | Year | Publisher | Language |
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Course activity | Pre-examination | Obligations | Number of points |
---|---|---|---|
Term paper | Yes | Yes | 40.00 |
Oral part of the exam | No | Yes | 60.00 |
Full Professor
Full Professor
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© 2024. Faculty of Technical Sciences.