Generative AI for a Neurodegenerative Condition: Multiple Sclerosis
Project ID: 2228cd1285 (You will need this ID for your application)
Under Offer
Research Theme: Healthcare Technologies
UCL Lead department: Computer Science
Lead Supervisor: Amid Ayobi
Project Summary:
Neurological conditions are on the rise and are recognised as a global public health challenge. There are 16.5M neurological cases in England costing the NHS about £4.4 billion per annum. Self-managing neurological conditions can significantly improve quality of life and inform clinical practice. However, symptoms affecting people’s vision, cognition, and mobility make self-managing neurological conditions difficult in everyday life.
Generative AI (GenAI) has significant potential to empower people with neurodegenerative conditions to self-manage their health and wellbeing in new conversational and accessible ways. GenAI systems, such as ChatGPT and DALL·E, are capable of automatically generating digital content based on human prompts. Customised GenAI could assist people with neurodegenerative conditions in engaging in self-care more effectively. However, there are limitations and risks, including bias, incorrect output, and a lack of personalisation.
This project will address current deficits of GenAI by focusing on multiple sclerosis (MS) self-management as an exemplar. This project will leverage the synergies of human-centred design and machine learning, pursuing the following objectives: (1) identify the GenAI needs of people with MS; (2) design novel interactive GenAI systems that support the needs of people with MS; (3) develop and evaluate prototypes of these systems with people with MS in daily life. A potential GenAI system could, for example, enable people with MS to use key word-based prompts to generate daily symptom summaries and adapt outputs according to their needs using text- and voice-based interfaces.
We will collaborate with the Queen Square Multiple Sclerosis Centre and the MS Society UK. The PhD candidate will have a background in computer science or related fields (e.g., machine learning, human-computer interaction, or digital health) and will become an expert of human-centred AI for health and wellbeing.