This course will introduce both design and methodologies required to develop digital technology for healthcare delivery from a patient's perspective. The course discusses the emerging role that digital technology plays in delivering support for mental health and wellbeing, managing long-term chronic health conditions by providing information to patients, and broadening access to medical services. The aim of this course is to give students an overview of human-centred digital healthcare technology, why it is important but difficult and how to start to address common challenges in it.

The course is divided into two parts.

(1) One part will introduce students to emerging areas of innovation in digital healthcare delivery, the nature of healthcare systems, the challenges that are faced by designers, and the techniques from human-computer interaction, psychology and social sciences that help to address them.

(2) The other part will introduce AI methodologies encompassing sensing, information processing and ML-based solutions for digital health care.

2 hours per week.

None

None

Exam worth 80%.

Coursework 1 (10%) - A portfolio exercise documenting the design of a digital healthcare technology

Coursework 2 (10%) - A report on the understanding, design and implementation of a digital healthcare technology.

The aim of this course is to give students an overview of digital healthcare technologies from the perspectives of design, development and delivery. The following are the Aims: [A1] Understand the components of AI-based decision making, and how to develop an AI-based pipeline for a given healthcare task. [A2] Learn emerging areas of innovation in digital healthcare delivery, the challenges faced by designers, and the techniques from HCI, psychology and social sciences that help to address them.

By the end of this course students will be able to:

1. Understand all components of AI-driven healthcare technologies and

2. Design, analyse and evaluate the pipeline of an AI-based healthcare system

3. Analyse new digital healthcare innovations and 1) identify potential problem areas (including design, AI implementation, and sensor reliability) then 2) respond with a plan using the techniques they have been taught to start to address those issues.

4. Appraise how inequalities in healthcare delivery are reinforced or mitigated depending on how we design digital healthcare.

Students must submit at least 75% by weight of the components (including examinations) of the course's summative assessment.