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FORESIGHT: A novel GPT-based pipeline trained on NHS data
February 7, 2023
Zeljko Kraljevic
outlines how these foundation models for medicine can provide the potential for a diverse integration of medical data that includes electronic health records, images, lab values, biologic layers such as the genome and gut microbiome...
Over the past four years, the AI world has surged ahead with large language models (LLMs), also known as “foundation models” which can be adapted to achieve many linguistic tasks. You’ve probably seen a plethora of articles in the media recently about some of these models (ChatGPT, Dalle-2), that can write coherent essays, write code, but also generate art and films, and many other capabilities.
With the NHS at breaking point, a critical question is whether these AI approaches could be used to improve care. Hospital records hold detailed information about each patient's health status and general clinical history, a large portion of which is stored within the unstructured text. Temporal modelling of this medical history, which considers the sequence of events, could be used to forecast and simulate future events, estimate risk, suggest alternative diagnoses or forecast complications.
I have developed
Foresight
as part of the
CogStack
platform, a novel GPT-based pipeline that is trained on NHS data to forecast future medical events such as disorders, medications, symptoms and interventions.
On tests in two large King’s Health Partner hospitals (King’s College Hospital, South London and Maudsley) and the US MIMIC-III dataset Foresight performed well when set challenges by clinicians. The model is being used for many uses including real-world risk estimation, virtual clinical trials and clinical research to study the progression of diseases, simulate interventions and counterfactuals, and for educational purposes.
Preprint:
https://arxiv.org/abs/2212.08072
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We’re thrilled to announce that John Jumper, PhD , will kick-off our 2024/2025 Seminar Series with his talk, "Extending AlphaFold to make predictions across the universe of biomolecular interactions" . John is one of the key pioneers behind the development of Google’s DeepMind AlphaFold - an artificial intelligence model to predict protein structures from their amino acid sequence with high accuracy. This in-person event promises to be an incredible opportunity to hear from one of the foremost innovators in AI and biology. Seminar Series Event: Extending AlphaFold to make predictions across the universe of biomolecular interactions Date and Time: 14:00 – 15.00, Thursday 10 October 2024 Location: The Council Room, 2nd floor, The King’s Building, Strand Campus Registration: Limited to EPSRC DRIVE-Health students in the first instance. Please email drive-health-cdt@kcl.ac.uk to check availability. Abstract: The high accuracy of AlphaFold 2 in predicting protein structures and protein-protein interactions raises the question of how to extend the success of AlphaFold to general biomolecular modeling, including protein-nucleic and protein-small molecule structure predictions as well as the effects of post-translational modification. In this talk, I will discuss our latest work on AlphaFold 3 to develop a single deep learning system that makes accurate predictions across these interaction types, as well as examine some of the remaining challenges in predicting the universe of biologically-relevant protein interactions.
We are thrilled to invite John Vardakis to speak at our EPSRC DRIVE-Health CDT's summer symposium next month. John joins us from Science Card to talk about " Exploring the Frontier: The future of GenAI Investments and Collaborations in Industry and Academia ." John Vardakis, PhD , has a diverse work experience, primarily in the field of scientific research. John is currently serving as the Head of Science Card Investment Group at Science Card, where they are involved in innovative banking. Previously, they worked as a Research Scientist at the University of Glasgow, where they focused on simulation-driven microelectromechanical systems design. John also worked as a Research Scientist at INSERM, investigating tumor mechanics and vascular fractality quantification. At the Center for Computational Imaging & Simulation Technologies in Biomedicine (CISTIB), they conducted research in cardiovascular and cerebrovascular biomechanics. Their work at UCL involved computational modeling of dementia and image-guided neurosurgery for epilepsy. John completed their DPhil in Biomedical Engineering at the University of Oxford, where their research focused on fluid transport in the brain. John also gained experience in the fields of vascular diagnosis and market research at the University of Heidelberg and P2i, respectively. Additionally, they worked as a Mechanical Engineer at Enactus and completed a placement at King's College London's Centre for Robotics Research. John Vardakis, PhD has a strong educational background in engineering and innovation. John obtained their Bachelor of Engineering (BEng) degree in Mechanical Engineering from King's College London in the years 2005 to 2008. John then pursued further education at the University of Oxford, where they completed the Centre for Doctoral Training in Healthcare Innovation from 2009 to 2010. Following this, they earned a Doctor of Philosophy (PhD) degree in Biomedical/Medical Engineering from the University of Oxford from 2010 to 2014. During their time at Oxford, they also pursued a diploma in Strategy & Innovation (Science Innovation Plus programme) from Saïd Business School, University of Oxford, from 2011 to 2012. In addition to their academic degrees, John Vardakis has obtained additional certifications. In December 2010, they received a Mathwork Training Certificate for completing the "Deploying MATLAB Based Applications - .NET Edition" course. John also obtained another Mathwork Training Certificate in December 2010 for completing the "MATLAB Programming Techniques" course. Registration is required, please email drivecdt@kcl.ac.uk for further event details. Our annual Symposium is a one-day face-to-face event for all DRIVE-Health students, academic supervisors, stakeholders and partners. Our aim is to discuss translating scientific and technological innovations in AI and data science, from research to clinical practice and commercial enterprise. The symposium will feature keynote talks, panel discussions, and poster presentations showcasing cutting-edge research and successful case studies. We will also celebrate our coming together with networking drinks at the end of the symposium. The EPSRC DRIVE-Health Centre for Doctoral Training is training the next generation of PhD health data scientists to become the innovation leaders of tomorrow. Our students work within an active NHS environment, and develop new models of data-driven care, whilst leveraging significant recent investment and infrastructure in Health Data Research within the UK. By registering for this event, you give consent to provide your name, e-mail address and registration information with King's College London for the purposes of managing the EPSRC DRIVE-Health CDT's Summer Symposium. Your personal data will be managed by those organisations and by Eventbrite according to their published privacy policies.
