Dr Kieran Zucker

Profile

I completed my BSc in Medical Sciences with Molecular Medicine at University College London (UCL) in 2009 undertaking research into the mRNA expression of Flavin Containing Monooxygenase knockout mice. I continued at UCL to complete my undergraduate medical degree in 2012.

During my time at UCL I worked as a research associate at the Centre for Evidence at Transplantation based at the Royal College of Surgeons conducting research into the rate of publication of randomised controlled trials in transplant medicine. I also undertook a Society for General Microbiology Studentship characterising the enzymatic properties of a previously unstudied bacteria implicated in cases of endocarditis.

I undertook my Foundation Training and Core Medical training in the Yorkshire region before being promoted early to the role of clinical oncology specialist registrar in 2016. During this time I was involved in a number of clinical research projects and had regular input in the management of patients enrolled in clinical trials.

I took up my role as Clinical Research Fellow based at the Leeds Institute for Data Analytics in 2017 before completing my PhD in Health Data Science and Machine Learning. In 2021 I took up my current role as an NIHR Clinical Lecturer working on a number of projects including cancer outcome prediction, computer vision, natural language processing, data visualisation, in silico trials and process mining.

I am a Fellow of the British Computing Society, A Leading Practitioner with the Federation of Informatics Professionals and a Fellow of the Royal College of Radiologists.

I hold a number of leadership roles locally as the Co-Director of the Centre for Doctoral Training in Medical AI, The Data Science and AI Lead for Leeds Cancer Research Centre and as the Clinical Lead for the Artificial Intelligence Community of Interest at Leeds Teaching Hospitals NHS Trust.

I hold further national positions as a member of the Radiology AI Faculty and the AI in Clinical Oncology Advisory Group at the Royal College of Radiologists. I am a member of the British Computing Society Medical AI group and sit on the Impact Committee for Health Data Research UK.

Responsibilities

• Data Science and AI Lead for Leeds Cancer Research Centre
• Co-Director Centre for Doctoral Training In Medical Artificial Intelligence Supervisor
• Medical Data Science and AI Training Lead West Yorkshire Deanery

Research interests

My main area of research interest is in the application of data science methods to routinely collected healthcare data and the translational artificial intelligence into routine clinical use. My work aims to make use of clinical data to develop tools with real world applicability and deliver their safe implementation into clinical settings. My research portfolio focusses on a large number of elements from the data science and machine learning development pipeline including data quality and provenance, algorithmic fairness and bias, interpretability, validation and in silico trials.

I currently engage in research based on structured data, natural language, digital histopathology, free text, joint image language models and time series data. I further collaborate on a number of national and international studies with a focus on harmonising data, adopting common data models and federated analysis.

I am also the creator and lead developer of AuguR, a cancer analytics web application allowing clinicians to interact with real world clinical data relating to oncology. This software is currently being further developed rolled out across the Yorkshire and Humber Region.

As part of my work to improve translation of data science I have created the Digital Health Hive a community of patients, carers, clinical professionals, academics, industry professionals and third sector organisations working to enhance and improve the quality and impact of digital health research.

• The Digital Health Hive

Qualifications

• PhD
• MBBS
• BSc (Hons)

Professional memberships

• Fellow of the British Computing Society
• Fellow of the Royal College of Radiologists
• Leading Practitioner at the Federation of Informatics Professionals
• Member of the Royal College of Physicians

Student education

Formal Teaching Roles:

Co-Director: Centre for Doctoral Training in Medical AI

Training Lead: Medical Data Science and AI – West Yorkshire Deanery

Lecturer: Ai content as part of Enquire MBBS programme

PhD Supervision:

Current and past PhD students

Jack Breen: AI in Ovarian Cancer Digital Histopathology

Rachael Harkness: Anomaly Detection in Thoracic Imaging

Alex Coles: Automated Detection f Cancer Recurrence Events in Longitudinal Records

Xin Ci Wong: Application of Generative Model for Bias Mitigation in Radiology AI

George Baker: Medical Visual Question Answering Models

David Marples: Machine Learning Forecasts of Unplanned Hospital Attendance

Other Post Graduate Supervision:

Current and past post-graduate supervision including at masters level and data science internships

Cathy Tomson

Millie Wagstaff

Wojciech Banas

Clinical Academic Supervision:

Current and past clinical academic Ai and Data Science supervision including at foundation and ACF level

Helen Ng

Isa Mahmood

Francis Aggrey

Daniel Maloney

Faisal Alshukri

Alice Spencer

Sophie Ashley

Christian Flynn

Antony Attia

Frederick Goddard

Sannah Jamil

Katheryn Orobosa-Ogbeide

Narrative Summary:

I designed and am the lead for the UK’s first accredited Foundation Program in Medical Data Science and Machine Learning Engineering which commences in 2023. I am also involved as a supervisor and the implementation of AI Clinical Fellowship posts in Yorkshire for Clinical Oncologists.

I am involved in a further range of educational activities across the university. I have been involved in the teaching of undergraduate medicals students since 2012 and have provided both formal and informal teaching in clinical medicine. My work with undergraduate medical students now predominantly focusses on Oncology related teaching. I also act as a PhD supervisor, MSc supervisor, MRES and LIDA data science intern supervisor. I contribute to supervision and teaching on the following programmes:

• Center for Doctoral Training In Medical Artificial Intelligence
• LIDA Data Science Internship Scheme
• MBBS Medicine
• Postgraduate Foundation Programme (Yorkshire and Humber Deanery)
• Postgraduate Internal Medicine Training Programme (Yorkshire and Humber Deanery)

I also increasingly deliver focussed teaching to clinical academics on data science with a particular focus on best practice approaches to coding.

Outside of the University I work with the Royal College of Radiologist on their Radiology AI Faculty to develop of data science and machine learning educational materials.

Research groups and institutes

• Leeds Institute of Medical Research at St James's