Applications of Neural Networks in Medicine (5 cr)
Code: TX00EY18-3002
General information
- Enrollment
-
05.05.2025 - 19.10.2025
Registration for implementation has not started yet.
- Timing
-
20.10.2025 - 14.12.2025
The implementation has not yet started.
- Number of ECTS credits allocated
- 5 cr
- Mode of delivery
- On-campus
- Unit
- School of ICT and Industrial Management
- Campus
- Karaportti 2
- Teaching languages
- Finnish
- Seats
- 0 - 35
- Degree programmes
- Information and Communication Technology
- Teachers
- Sakari Lukkarinen
- Juha Kopu
- Groups
-
TVT23-HHyvinvointi- ja terveysteknologia
- Course
- TX00EY18
Objective
After completing the course, the student understands the basics of neural network operation, is able to create neural network models implemented in Python for medical applications (including the classification of medical images and natural language processing) and knows the basics of using software as a medical device.
Content
Software as a medical device
Fundamentals of neural networks, convolutional and feedback neural networks
Medical applications
Python programming
Ethical aspects of technology application and liability issues
Evaluation scale
0-5
Assessment criteria, satisfactory (1)
Student has achieved the course objectives. Student will be able to identify, define and use the course subject area’s concepts and models. Student understands the criteria and principles of the expertise development.
Assessment criteria, good (3)
Student has achieved the course objectives well, even though the knowledge and skills need improvement on some areas. Student is able to define the course concepts and models and is able to justify the analysis. Student is able to apply his/her knowledge in study and work situations. Student understands the importance of expertise in the field of information and communication technology and is able to analyze his/her own expertise.
Assessment criteria, excellent (5)
Student has achieved the objectives of the course with excellent marks. Student masters commendably the course subject area’s concepts and models. Student is able to make justified and fluent analysis and to present concrete development measures. Student is well prepared to apply his/her knowledge in study and work situations. Student is able to analyze expertise in the information and communication technology sector and the development of his/her own expertise.
Assessment criteria, approved/failed
Student has achieved the course objectives. Student will be able to identify, define and use the course subject area’s concepts and models. Student understands the criteria and principles of the expertise development.
Objective
After completing the course, the student understands the basics of neural network operation, is able to create neural network models implemented in Python for medical applications (including the classification of medical images and natural language processing) and knows the basics of using software as a medical device.
Content
Software as a medical device
Fundamentals of neural networks, convolutional and feedback neural networks
Medical applications
Python programming
Ethical aspects of technology application and liability issues