Two new artificial intelligence projects launched with Faculty AI
4 Jul 2022, 9:47 a.m.
Two new projects will dive into the potential of GOSH’s data to accelerate research and improve patient outcomes.
The Digital Research, Innovation and Virtual Environments (DRIVE) unit at Great Ormond Street Hospital (GOSH) is excited to welcome two fellows from Faculty, a leading British AI company which runs the Faculty Fellowship Programme.
Hospitals across the world collect information every day to guide care and treatments. GOSH is no different, and we are improving the ways we collect, store and understand data.
Understanding lab results
Dr Omar Jahangir will work on a project to develop a new approach for understanding lab results, which could lead to them being used more effectively in research to guide diagnosis and treatment decisions. This is particularly important for GOSH patients as children and young people often have rare conditions. This means typical ranges for lab results are uninformative or misleading, and conditions can be hard to diagnose.
The project involves several steps, including understanding which lab results are most important, developing an AI model for identifying abnormal lab results, and validating how good the model is at uncovering abnormalities in the data. The data is fully anonymised so patients can’t be identified from their real-life lab results.
Omar has a PhD in Machine Learning and Particle Physics from University College London and has previously done an internship with a healthcare provider.
I’m very excited by the opportunity to explore the value of this data to understand how it could be used to its full potential for the benefit of the children and young people who are seen at GOSH.
Developing support for decision-making
Dr David Peinador-Veiga will work on a project to investigate and test a new way of using data to help clinicians predict treatment routes. It will explore how information on diagnosis and medical procedures interact, and then analyse certain diagnoses and medical procedures in detail to understand what makes them more likely to be required and when. Unlike the lab results data, this data is randomised, which means it is like real-life data, but made up.
David has a PhD in Theoretical Physics from Queen Mary University of London and has experience with many data science projects including prediction modelling, uncertainty analysis, and machine learning techniques.
I’m looking forward to applying my skills to the world of healthcare. I hope that my project can help GOSH to better understand new ways that data can be used to improve treatment and care for children and young people.
Faculty builds and deploy market leading AI technology to enable decision intelligence across the NHS (Frontier) as well as hosting a Fellowship Programme which sees academics in science, technology, engineering and mathematics (STEM) given training at Faculty, before beginning a placement as a data scientist at a host company, such as GOSH.
We are delighted to have kicked off our partnership with GOSH which marks the start of an exciting collaboration and the beginning of an interesting journey to understand GOSH data in order to enhance patient care.