Artificial Medical Intelligence Group (AMIGO) at King's College London (KCL)

We are the Artificial Medical Intelligence Group (AMIGO).

AMIGO is based in the School of Biomedical Engineering and Imaging Sciences at King’s College London (KCL), UK.

Research Themes

Advancing medical AI through interdisciplinary research

Our research focuses on developing artificial intelligence solutions for real-world medical challenges. We combine cutting-edge machine learning with clinical expertise to create tools that improve patient care and advance medical knowledge.

Medical AI & Machine Learning

Developing advanced deep learning algorithms for medical image analysis, clinical decision support, and predictive modeling using large-scale healthcare datasets.

Medical Imaging

Creating AI-powered tools for automated analysis of MRI, CT, and other medical imaging modalities to assist radiologists and improve diagnostic accuracy.

Clinical Translation

Bridging the gap between research and clinical practice by developing deployable AI systems that integrate seamlessly into hospital workflows.

Multidisciplinary Collaboration

Bringing together computer scientists, engineers, clinicians, and mathematicians to tackle complex medical challenges from multiple perspectives.

Open Science

Promoting reproducible research through open-source software development, public datasets, and transparent methodologies that benefit the global research community.

Healthcare Analytics

Leveraging large-scale hospital data to identify patterns, predict outcomes, and optimize healthcare delivery through advanced statistical and machine learning methods.

Current Research Projects

Ongoing research initiatives and their impact

Explore our active research projects that are advancing the field of medical artificial intelligence and improving patient outcomes.

Federated Learning Interoperability Platform (FLIP)

Collaborative Research Projects

Partnerships driving medical AI innovation

Our collaborative projects bring together academic institutions, healthcare providers, and industry partners to advance medical AI research and clinical implementation.