PhD Studentship: Developing Geospatial Accessibility Models for Healthcare Facilities to Improve Access for People with Disabilities

Project Overview

This innovative PhD project focuses on improving healthcare accessibility for people with disabilities in the UK by creating a geospatial accessibility model powered by advanced machine learning techniques. Key features of the project include:

• Big Data Integration: Leveraging publicly available datasets like OpenStreetMap (OSM), WheelMap, and patient reviews (e.g., Yelp) to analyse healthcare facility infrastructure and user feedback.
• Accessibility Scoring: Developing tools to assess and score facilities based on their accessibility, with an initial focus on wheelchair users and potential adaptability for other disabilities.
• Advanced AI Methods: Using cutting-edge tools like Transformer-based masked autoencoders to identify complex patterns and generate actionable insights.
• Real-World Application: Designing a user-friendly web or mobile application to help individuals and caregivers make informed healthcare decisions.

The project is a collaboration between the International Centre for Evidence in Disability (ICED) at LSHTM and the Birkbeck Data Science and AI Institute (BIDA+). Validation will involve user testing with individuals with disabilities and caregivers to ensure practical and impactful outcomes. Insights will inform urban planning and healthcare policy, delivering data-driven recommendations to improve accessibility.

Key Subject Areas and Keywords

Healthcare Accessibility | Machine Learning | Big Geospatial Data | Disability Inclusion

Supervisory Team

Principal Supervisor: Dr Paul Yoo | Email: p.yoo@bbk.ac.uk  

Co-Supervisor: Prof. Hannah Kuper | Email: hannah.kuper@lshtm.ac.uk

Further information

Please contact Dr Paul Yoo for further information about the project. Further details regarding the application process can be obtained by contacting the Faculty of Science PGR team ( science-pgr@bbk.ac.uk)

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