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DEGREE REGULATIONS & PROGRAMMES OF STUDY 2024/2025

Timetable information in the Course Catalogue may be subject to change.

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DRPS : Course Catalogue : School of Informatics : Informatics

Undergraduate Course: Topics in Biomedical Informatics (UG) (INFR11282)

Course Outline
SchoolSchool of Informatics CollegeCollege of Science and Engineering
Credit level (Normal year taken)SCQF Level 11 (Year 4 Undergraduate) AvailabilityAvailable to all students
SCQF Credits10 ECTS Credits5
SummaryThis course follows the delivery and assessment of Topics in Biomedical Informatics (INFR11263) exactly. Undergraduate students must register for this course, while MSc students must register for INFR11263 instead.
Course description This course follows the delivery and assessment of Topics in Biomedical Informatics (INFR11263) exactly. Undergraduate students must register for this course, while MSc students must register for INFR11263 instead.
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Other requirements None
Information for Visiting Students
Pre-requisitesNone
Course Delivery Information
Academic year 2024/25, Available to all students (SV1) Quota:  None
Course Start Semester 2
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 100 ( Lecture Hours 9, Seminar/Tutorial Hours 9, Feedback/Feedforward Hours 2, Summative Assessment Hours 2, Programme Level Learning and Teaching Hours 2, Directed Learning and Independent Learning Hours 76 )
Assessment (Further Info) Written Exam 100 %, Coursework 0 %, Practical Exam 0 %
Additional Information (Assessment) 100% Exam
Feedback
One session will be dedicated to an example topic. A practice assessment question will then be set with time to do this and submit. There will be a debrief in a class room session as well as individual feedback on submitted work.
Exam Information
Exam Diet Paper Name Hours & Minutes
Main Exam Diet S2 (April/May)Topics in Biomedical Informatics (PG INFR11263/ UG INFR11282) & Foundational Biomedical AI research PG (INFR11262):120
Learning Outcomes
On completion of this course, the student will be able to:
  1. Critically assess the challenges associated with biomedical data analysis and modelling across a variety of contexts, in particular with respect to noise in the data, patient stratification and regulatory and ethical issues.
  2. Critically discuss and compare data acquisition, analysis and modelling protocols.
  3. Present and explain biomedical data problems and appropriate analysis in one area of biomedicine to an interdisciplinary audience.
Reading List
None
Additional Information
Graduate Attributes and Skills Research and enquiry: problem-solving, critical/analytical thinking, handling ambiguity, knowledge integration.
Personal responsibility and autonomy: ethics and social responsibility, independent learning, self-awareness and reflection, creativity, decision-making.
Communication: interpersonal/teamwork skills; verbal, written, and cross-disciplinary communication.
KeywordsTBI (UG),Shadow course
Contacts
Course organiserDr Andrea Weisse
Tel: (0131 6)51 1211
Email: Andrea.Weisse@ed.ac.uk
Course secretaryMiss Yesica Marco Azorin
Tel: (0131 6)50 5194
Email: ymarcoa@ed.ac.uk
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