Featured Event: Prof Venet Osmani Inaugural Lecture
Venet is Professor of Clinical AI and Machine Learning at the Digital Environment Research Institute (DERI), Queen Mary University of London. The title of the lecture is From code to bedside: A journey towards realising Generalist Clinical AI
Abstract:
We are on the cusp of a major revolution in healthcare. Just as the microscope opened a whole new, previously unseen world, clinical AI is providing unprecedented health insights by combing through vast amounts of data. Translating these insights into real-world clinical applications is the next frontier towards the vision of Generalist Clinical AI (GCAI), which refers to AI systems with human-level capabilities to support clinical decision-making. While the complete realisation of this ambitious vision is still on the horizon, significant progress has already been made.
This lecture will trace my career path, from early work in mental health, chronic diseases (including neurodegenerative conditions), cancer, and critical care to its evolution alongside AI advancements. I will also highlight the capabilities and challenges associated with incorporating wearable devices and clinical data (biomarkers, medical imaging, and omics) in this research, while acknowledging the importance of addressing algorithmic bias and health inequalities. Furthermore, democratising access to clinical data is paramount to accelerate research. I will explore the role of synthetic clinical data in this context.
To conclude, I will share my perspective on how these aspects can be integrated to realise the GCAI vision.
Biography:
Venet Osmani is a Professor of Clinical AI and Machine Learning at Queen Mary University of London, directing the Osmani Lab within Digital Environment Research Institute (DERI).
He is also a Visiting Professor at the University of Sheffield, where he directed the 40-member Health Informatics Research Group, served on the Executive Board of the Healthy Lifespan Flagship Institute (HELSI), and was a Research Board member of the Insigneo Institute. He also co-directed a Wellcome-funded Doctoral Training Centre on Public Health.
Prof Osmani’s interdisciplinary research focuses on the analysis of large-scale, longitudinal health records, including biomarkers, imaging, multi-omics, and routine care data to optimise treatment strategies, improve patient care, and mitigate health inequities. Apart from clinical data, his work also focuses on incorporating human behaviour data, generated from wearable devices and smartphones, with a particular focus on mental health. Methodological research includes generative architectures (such as GANs, VAEs, and Diffusion Models) for synthetic patient data, explainable AI methods, and sample complexity.
Prof Osmani’s work has been featured in MIT Technology Review, The Telegraph, Le Figaro, Forbes, and other media outlets. The lab is funded by UKRI's Medical Research Council (MRC), Engineering and Physical Sciences Research Council (EPSRC), National Institute for Health and Care Research (NIHR), British Heart Foundation (BHF), and the European Commission (from FP7 to Horizon Europe).
Prof Osmani is also an invited Expert Evaluator for European Commission (Horizon Europe, Horizon 2020, FET Open / EIC Pathfinder, MSCA Programmes), UK's Medical Research Council (MRC), UK's National Institute for Health Research (NIHR), UK’s Medical Research Foundation (MRF), Swiss National Science Foundation (SNSF). He collaborates with leading clinical institutions, including Mayo Clinic (FL), Cleveland Clinic (OH), Mount Sinai Hospital (NY), Great Ormond Street Hospital for Children, as well as several leading research institutions.
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