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Andrew  King

Dr Andrew King

Reader in Medical Image Analysis

Research interests

  • Imaging sciences

Biography

Dr King received a BSc. (Hons) degree in Computer Science from Manchester University in 1989, an MSc. (with distinction) in Cognition, Computing and Psychology from Warwick University in 1992, and a PhD degree in Computer Science from Warwick University in 1997. From 2001-2005 he worked as an Assistant Professor in the Computer Science department at Mekelle University in Northern Ethiopia. Since 2006 he has worked in the School of Biomedical Engineering & Imaging Sciences at King's, focusing on machine learning and medical image analysis.

    Research

    AdobeStock_276394749
    Centre for Doctoral Training in Digital Twins for Healthcare

    DT4Health brings together a world-class multidisciplinary team of supervisors to train future innovation leaders to articulate and materialise the Digital Twin vision in healthcare.

    News

    New artificial intelligence tool automates analysis of large-scale cardiac scan databases

    King’s researchers have proposed and validated the first start-to-end pipeline for fully automated analysis of large, unstructured clinical and research...

    AI cardiac look and feel

    New open-source AI tool supports clinicians to interpret lung ultrasounds

    Researchers at King’s College London have developed a real-time AI-enabled lung ultrasound tool which can assist non expert clinicians in interpreting scans...

    close up of a person's hands as they operate an ultrasound machine

    King's researchers gather for workshop on applying AI to microscopy and imaging

    The King's Institute for Artificial Intelligence hosted a workshop for researchers to explore how artificial intelligence can be applied in microscopy and...

    Robert Knight stands at a podium and speaks into a microphone

    AI models can be racially biased when trained on unbalanced data sets, researchers find

    They found that where AI models are used, misdiagnoses would occur for under or non-represented races

    unbalanced-datajpg

    Events

    18JanBush House

    Applying AI Methods to Microscopy and Imaging

    This event brings together bioscientists who want to use AI based methods for image analysis with computational scientists and mathematicians.

    Please note: this event has passed.

      Research

      AdobeStock_276394749
      Centre for Doctoral Training in Digital Twins for Healthcare

      DT4Health brings together a world-class multidisciplinary team of supervisors to train future innovation leaders to articulate and materialise the Digital Twin vision in healthcare.

      News

      New artificial intelligence tool automates analysis of large-scale cardiac scan databases

      King’s researchers have proposed and validated the first start-to-end pipeline for fully automated analysis of large, unstructured clinical and research...

      AI cardiac look and feel

      New open-source AI tool supports clinicians to interpret lung ultrasounds

      Researchers at King’s College London have developed a real-time AI-enabled lung ultrasound tool which can assist non expert clinicians in interpreting scans...

      close up of a person's hands as they operate an ultrasound machine

      King's researchers gather for workshop on applying AI to microscopy and imaging

      The King's Institute for Artificial Intelligence hosted a workshop for researchers to explore how artificial intelligence can be applied in microscopy and...

      Robert Knight stands at a podium and speaks into a microphone

      AI models can be racially biased when trained on unbalanced data sets, researchers find

      They found that where AI models are used, misdiagnoses would occur for under or non-represented races

      unbalanced-datajpg

      Events

      18JanBush House

      Applying AI Methods to Microscopy and Imaging

      This event brings together bioscientists who want to use AI based methods for image analysis with computational scientists and mathematicians.

      Please note: this event has passed.