GD5302 Health Data Science Practice

Academic year

2024 to 2025 Semester 2

Further information on which modules are specific to your programme.

Key module information

SCOTCAT credits

30

The Scottish Credit Accumulation and Transfer (SCOTCAT) system allows credits gained in Scotland to be transferred between institutions. The number of credits associated with a module gives an indication of the amount of learning effort required by the learner. European Credit Transfer System (ECTS) credits are half the value of SCOTCAT credits.

SCQF level

SCQF level 11

The Scottish Credit and Qualifications Framework (SCQF) provides an indication of the complexity of award qualifications and associated learning and operates on an ascending numeric scale from Levels 1-12 with SCQF Level 10 equating to a Scottish undergraduate Honours degree.

Availability restrictions

Open to MSc Digital Health students only.

Planned timetable

To be arranged

This information is given as indicative. Timetable may change at short notice depending on room availability.

Module coordinator

Dr D C C Harris-Birtill

This information is given as indicative. Staff involved in a module may change at short notice depending on availability and circumstances.

Module Staff

Team taught; teaching staff confirmed at start of semester.

This information is given as indicative. Staff involved in a module may change at short notice depending on availability and circumstances.

Module description

The digital transformation of healthcare is creating a need for skilled professionals with the expertise to lead innovations in technology use and data analysis. This module brings together academic staff and external partners from technical and clinical backgrounds to provide a breadth of learning that encompasses real clinical problems and the solutions that Health Data Science can provide. You will learn about the practical applications of Health Data Science and the practical skills in medical data analysis and in the use of digital technologies needed to address healthcare challenges. You will develop your understanding of techniques for programmatically processing medical data such as genetic data, medical images, and patient vital signs. You will also learn about Health Data Science governance and the ethical considerations that can arise when designing and executing medical data analysis studies and when applying digital health techniques to solve real-world medical problems.

Relationship to other modules

Pre-requisites

BEFORE TAKING THIS MODULE YOU MUST PASS GD5301

Assessment pattern

100% Coursework

Re-assessment

Coursework = 100%

Learning and teaching methods and delivery

Weekly contact

Usually 1 x 2 hour lecture every week; 1 x practical class every second week; additional skills workshops in some weeks.

Scheduled learning hours

45

The number of compulsory student:staff contact hours over the period of the module.

Guided independent study hours

251

The number of hours that students are expected to invest in independent study over the period of the module.

Intended learning outcomes

  • Be familiar with various health data science and digital health concepts, such as image analysis in medical imaging and understand how to practically solve these problems.
  • Have gained experience in programmatically processing medical data (such as medical images, DNA data and vital signs).
  • Have gained a practical understanding of data analysis techniques applied to medical data.
  • Understand the practical issues, including ethical considerations, that can arise when designing and implementing medical data analysis studies.