Professional/Short course Disease, Diagnosis and Monitoring
15 credit level 7 module
Introduction
This 15 credit module, Disease, Diagnosis and Monitoring, will introduce you to the key chronic disease conditions that will benefit from advances in artificial intelligence (AI) and digital technologies.
In each subject area, disease pathology, screening, diagnosis, monitoring and prognosis will be discussed from the perspective of existing health technology and their associated limitations. This will be discussed together with respect to how AI and digital medicine has the potential to dramatically change and improve these clinical tools, ultimately improving healthcare and the associated economic burden.
On successful completion of this level 7 (Masters level) module, you will be able to:
- critically evaluate biomedical data in the investigation and diagnosis of disease and discuss the origin and effects of an abnormal biochemical profiles
- write informed practical reports that critically evaluate practical data with a focus on data integrity and analysis
- communicate how an understanding of pathology is important to critically evaluate the clinical utility of current diagnostic tool
- assess the unmet clinical need for the development of new technologies using AI in areas where existing technology fails to achieve diagnostic power.
Structure
Content
The module syllabus typically includes the following:
- Respiratory disease: Diagnosis and monitoring.
- Cancer: Clinical markers of disease together with physical imaging techniques.
- Cardiovascular disease: Lifestyle choices and disease pathology and how damage to the cardiovascular system is clinically assessed.
- Red blood cell disorders: Sickle cell disease and other anaemias - diagnostic and monitoring approaches.
- Diabetes: Screening, monitoring and diagnosis of Type II diabetes and new technology such as wearables and mobile Apps (M health).
- Mental health: Living well with dementia, robotics and smart technology.
- Musculoskeletal: New technological advances for medical implant functionalisation.
- Infectious disease: COVID-19 and bacterial infection.
Learning and Teaching
This module will be delivered through integrated lectures, where each lecture will provide the basic underpinning of each chronic disease, highlighting the unmet clinical need that AI or digital technology can address.
Several classes will be included that are linked to the lecture series offering students an applied understanding of each topic section.
Sessions are delivered on Frenchay Campus with the exception of one practical session on Respiratory/Cardiovascular Physiology and Diagnostics which will be on Glenside Campus.
Assessment
Assessment for this module comprises two parts:
- A practical case study report of 1,500 words to evidence how several biomedical fields all contribute to a diagnosis.
- A poster which will detail the pathology of a particular disease and how it can be differentially diagnosed together with the limitations of current technology. You will also be required to defend this poster in an oral defence (20 minutes).
Formative assessment is embedded in the tutorial sessions that develops the students pitching and communication skills.
Features
Study facilities
The College of Health, Science and Society has an excellent reputation for the quality of its teaching and the facilities it provides.
You'll have access to a range of on-campus and online facilities to support your learning, including the University Library which is open 24 hours a day.
Take a personalised virtual tour of the Health Professions facilities and experience what a typical day could look like here for you.
Prices and dates
Supplementary fee information
Please visit full fee information to see the price brackets for our modules.
Dates
Please click on the Apply Now button to view dates.
How to apply
Please click on the Apply Now button to apply online for your CPD modules, which you can take as stand-alone courses or as part of an undergraduate (level 3) or postgraduate (Masters level) programme.
For further information
- Email: pd@uwe.ac.uk
- Telephone: +44 (0)117 32 81158