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 abnormal profiles.
• communicate an understanding of disease pathology and the basis of current diagnostic techniques and assess the unmet clinical need for new health technologies to improve diagnostic power, monitoring or effective treatment.

Careers / Further study

This module can contribute towards the PGCert Health and Social Care, MSc Clinical Practice, and the Professional Development Awards. If you have any queries, please contact the Professional Development team (pd@uwe.ac.uk).

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 a poster which should illustrate the underlying pathology of the disease area being addressed and explain the biological and methodological principles underlying the current diagnostic approach or technology covered in one of the four practical classes on the module. 

You should present your own analysed data and interpretation from the practical session, and dedicate a section to exploring the scope for new and future technological or digital approaches for disease diagnosis, monitoring or treatment in the chosen area, including examples. You will present this poster in an oral defence.