Postgraduate Course: Individual Research Project (Biomedical AI) (INFR11197)
Course Outline
| School | School of Informatics |
College | College of Science and Engineering |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
| Course type | Dissertation |
Availability | Not available to visiting students |
| SCQF Credits | 80 |
ECTS Credits | 40 |
| Summary | The course is the main MSc project for the proposed MSc (Res) in Biomedical Artificial Intelligence. It will offer students the opportunity to gain in-depth experience of research in an interdisciplinary environment, with joint supervision from an AI and a biomedical specialist. |
| Course description |
The course is an individual research project where the students will work independently on an application of Artificial Intelligence to a biomedical problem. All projects will have joint supervision from an AI and a biomedical expert, enabling the student to work in an interdisciplinary environment and be embedded within the application. A particular feature of this course will be its attention to the societal and ethical aspects of the proposed research, which will form part of the assessment for the responsible innovation course.
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Course Delivery Information
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| Academic year 2019/20, Not available to visiting students (SS1)
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Quota: None |
| Course Start |
Block 5 (Sem 2) and beyond |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
800
(
Lecture Hours 2,
Seminar/Tutorial Hours 2,
Dissertation/Project Supervision Hours 20,
Feedback/Feedforward Hours 2,
Programme Level Learning and Teaching Hours 16,
Directed Learning and Independent Learning Hours
758 )
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| Assessment (Further Info) |
Written Exam
0 %,
Coursework
100 %,
Practical Exam
0 %
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| Additional Information (Assessment) |
100% Coursework.«br /»
«br /»
The course assessment will consist of a written dissertation to be independently marked by two examiners, in line with standard MSc requirements. The dissertation will address the following:«br /»
«br /»
- motivation: why is the problem tackled important?«br /»
- background: what are the necessary AI and biomedical knowledge?«br /»
- originality: what is different in what is proposed?«br /»
- implications: what is the impact of the research, both scientifically and more broadly in terms of its societal implications?«br /»
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| Feedback |
Feedback on assessed coursework will be provided within two weeks, and will include formative comments on work in relation to concepts studied in the course.
Report drafts will be reviewed by peers, the course instructor, the TA, and individual supervisors under a provided rubric. |
| No Exam Information |
Learning Outcomes
On completion of this course, the student will be able to:
- Be able to independently identify and apply appropriate AI algorithms to specific biomedical problems.
- Communicate effectively, both in writing and orally, technical AI concepts to an interdisciplinary audience of biomedical scientists.
- Discuss critically the broader societal and ethical implications of AI research in the biomedical field and in the specialised area of the project.
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Additional Information
| Graduate Attributes and Skills |
The course will provide the students with in-depth technical skills in one area of biomedical AI, as well as developing their problem solving and programming skills. As the course entails independent (but supervised) research, the students will gain considerably in terms of self-management skills (timetabling, independence in finding resources, etc). Through the course, the student will gain considerable experience of research in an interdisciplinary environment. Therefore, the students will improve their interdisciplinary communication skills. |
| Keywords | BAI-IP,CDT-BAI |
Contacts
| Course organiser | Prof Guido Sanguinetti
Tel: (0131 6)50 5136
Email: |
Course secretary | |
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