13E053SOM - Decision Making Systems in Medicine
Course specification | ||||
---|---|---|---|---|
Course title | Decision Making Systems in Medicine | |||
Acronym | 13E053SOM | |||
Study programme | Electrical Engineering and Computing | |||
Module | Biomedical and Environmental Engineering, Physical Electronics - Biomedical and Environmental Engineering, Physical Electronics - Biomedical and Nuclear Engineering, Physical Electronics - Nanoelectronics and Photonics | |||
Type of study | bachelor academic studies,master academic studies | |||
Lecturer (for classes) | ||||
Lecturer/Associate (for practice) | ||||
Lecturer/Associate (for OTC) | ||||
ESPB | 6.0 | Status | elective | |
Condition | none | |||
The goal | The objective of the course is for students to master basic methods for feature selection and extraction, statistical pattern recognition techniques in the medical domain, neural networks for decision-making in medicine, as well as means of evaluataion of designed decision-making systems. | |||
The outcome | Upon completion of the course, students will have skills related to the selection of relevant features and the formulation of high-quality training/testing sets, the design and testing of appropriate decision systems, as well as basic techniques for feature classification and clustering. | |||
Contents | ||||
URL to the subject page | https://automatika.etf.bg.ac.rs/sr/13e053som | |||
URL to lectures | https://teams.microsoft.com/l/team/19%3Al3hvwNFoTadTV0IW6wHFDmBz77KIXOFPSIL6G9rAbrs1%40thread.tacv2/conversations?groupId=ca7944ef-362e-4238-a31e-445d615c7df3&tenantId=1774ef2e-9c62-478a-8d3a-fd2a495547ba | |||
Contents of lectures | Random variables and random vectors. Feature extraction and selection methods. Hypothesis testing using Bayesian analysis. Design of linear and quadratic parametric classifiers. Design of nonparametric classifiers. Decision trees. Fundamentals of neural networks. | |||
Contents of exercises | Mastering software support (Phyton) for selecting the most informative attributes in the decision-making process, designing decision-making systems, as well as assessing the efficiency of synthesized systems, and in the context of decision-making in medicine by considering relevant databases. | |||
Literature | ||||
| ||||
Number of hours per week during the semester/trimester/year | ||||
Lectures | Exercises | OTC | Study and Research | Other classes |
3 | 1 | 1 | ||
Methods of teaching | Lectures (45), auditory exercises (15) and computer exercises (15). | |||
Knowledge score (maximum points 100) | ||||
Pre obligations | Points | Final exam | Points | |
Activites during lectures | 0 | Test paper | 70 | |
Practical lessons | 30 | Oral examination | 0 | |
Projects | ||||
Colloquia | 0 | |||
Seminars | 0 |