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Jorge Cardoso

Dr Jorge Cardoso

Reader

Research interests

  • Imaging sciences

Biography

M Jorge Cardoso is a Reader in Artificial Medical Intelligence at King’s College London, where he leads a research portfolio on big data analytics, quantitative radiology and value based healthcare. Jorge is also the CTO of the new London Medical Imaging and AI Centre for Value-based Healthcare.

Prior to King’s, Dr Cardoso was a Lecturer at UCL, Technical Lead of the Quantitative Radiology Initiative at the National Hospital for Neurology and Neurosurgery (NHNN), and Engineering Lead of the Neuro-oncology Flagship Programme at UCL, Institute of Healthcare Engineering.

He has more than 12 years expertise in advanced image analysis, big data, and artificial intelligence, and co-leads the development of NiftyNet, a deep-learning platform for artificial intelligence in medical imaging. He is also a founder of BrainMiner, a medtech startup aiming to bring quantitative biomarkers and predictive models to neurological care.

    News

    Radiology AI MedTech company deepc joins MONAI

    deepc, a leading MedTech company in radiology AI, has announced its strategic alignment, compatibility, and commitment towards MONAI, the Medical Open Network...

    MONAI logo

    King's accelerates synthetic brain 3D image creation using AI models powered by Cambridge-1 supercomputer

    King’s, along with partner hospitals and university collaborators, unveiled new details today about one of the first projects on Cambridge-1, the United...

    AI-supercomputer

    New MONAI tool eases the development of AI-assisted annotation models

    The Medical Open Network for AI (MONAI) has released MONAI Label v0.1, an intelligent image labelling tool that speeds up the creation of annotated datasets...

    MONAI_Blog-1.v1

    Changes should be made to routine scans for brain tumours, say researchers

    A new Position Statement from UK stakeholders highlights evidence gaps for routine follow up brain tumor imaging, but paves the way for evidence-based imaging

    brain imaging

    Federated learning may provide a solution for future digital health challenges

    Federated learning could address the key issues related to the storage and use of sensitive medical data .

    shutterstock_453502543

    Helping to build the UK's most powerful supercomputer for AI in healthcare

    King’s College London and Guy's and St Thomas' NHS Foundation Trust have been announced as founding partners of NVIDIA’s Cambridge-1, UK’s most powerful...

    Webp.net-resizeimage-2

    2020 BMEIS Postgraduate Research Symposium: Student-led symposium highlights postgraduate research excellence

    This year’s School of Biomedical Engineering & Imaging Sciences Postgraduate Research Symposium, for the first time held online, on 21 July, attracted up to...

    Logo of the 2020 BMEIS PGR Symposium

    MONAI update accelerates the pace of innovation for AI development

    MONAI v0.2 brings new capabilities, examples, and research implementations for medical imaging researchers.

    MONAI Logo

    AI Centre scales infrastructure to speed machine learning research

    An innovative software platform is helping the AI Centre increase the speed at which it can train AI algorithms and get the best use out of its powerful...

    Programming code and computer servers

      News

      Radiology AI MedTech company deepc joins MONAI

      deepc, a leading MedTech company in radiology AI, has announced its strategic alignment, compatibility, and commitment towards MONAI, the Medical Open Network...

      MONAI logo

      King's accelerates synthetic brain 3D image creation using AI models powered by Cambridge-1 supercomputer

      King’s, along with partner hospitals and university collaborators, unveiled new details today about one of the first projects on Cambridge-1, the United...

      AI-supercomputer

      New MONAI tool eases the development of AI-assisted annotation models

      The Medical Open Network for AI (MONAI) has released MONAI Label v0.1, an intelligent image labelling tool that speeds up the creation of annotated datasets...

      MONAI_Blog-1.v1

      Changes should be made to routine scans for brain tumours, say researchers

      A new Position Statement from UK stakeholders highlights evidence gaps for routine follow up brain tumor imaging, but paves the way for evidence-based imaging

      brain imaging

      Federated learning may provide a solution for future digital health challenges

      Federated learning could address the key issues related to the storage and use of sensitive medical data .

      shutterstock_453502543

      Helping to build the UK's most powerful supercomputer for AI in healthcare

      King’s College London and Guy's and St Thomas' NHS Foundation Trust have been announced as founding partners of NVIDIA’s Cambridge-1, UK’s most powerful...

      Webp.net-resizeimage-2

      2020 BMEIS Postgraduate Research Symposium: Student-led symposium highlights postgraduate research excellence

      This year’s School of Biomedical Engineering & Imaging Sciences Postgraduate Research Symposium, for the first time held online, on 21 July, attracted up to...

      Logo of the 2020 BMEIS PGR Symposium

      MONAI update accelerates the pace of innovation for AI development

      MONAI v0.2 brings new capabilities, examples, and research implementations for medical imaging researchers.

      MONAI Logo

      AI Centre scales infrastructure to speed machine learning research

      An innovative software platform is helping the AI Centre increase the speed at which it can train AI algorithms and get the best use out of its powerful...

      Programming code and computer servers