Dr Kieran Zucker
- Position: NIHR Clinical Lecturer and Honorary Clinical Oncology Specialist Registrar
- Areas of expertise: Oncology; Data Science; Machine Learning; Routinely Collected Data; Statistical Computing; Predictive Modelling; Comorbidity; Natural Language Processing; Computer Vision; Artificial Intelligence
- Email: K.Zucker@leeds.ac.uk
- Location: 11.80 Worsley Building
- Website: | ORCID
Dr Zucker completed his 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. He continued at UCL to complete his undergraduate medical degree in 2012. During his time at UCL Dr Zucker 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. He also undertook a Society for General Microbiology Studentship characterising the enzymatic properties of a previously unstudied bacteria implicated in cases of endocarditis.
Dr Zucker undertook his 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 he was involved in a number of clinical research projects and had regular input in the management of patients enrolled in clinical trials. Dr Zucker took up his role as Clinical Research Fellow based at the Leeds Institute for Data Analytics in 2017 before completing his PhD in Health Data Science and Machine Learning. In 2021 he took up his 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. Dr Zucker is a Fellow of the Faculty of Clinical Informatics where he has co-founded the Early Career Group and sits on the steering group for the Faculty’s Artificial Intelligence Specialist Interest Group. He is also a member of Royal College of Radiologists Clinical Oncology Artificial Intelligence Advisory Group.
- Center for Computational Imaging & Simulation Technologies in Biomedicine: Core Clinical Academic
- Centre for Doctoral Training In Medical Artificial Intelligence Supervisor
- LIDA Data Science Intern Supervisor
Dr Zucker’s main area of interest is in translational data science and artificial intelligence. His work aims to make use of clinical data to develop tools with real world applicability and deliver their safe implementation into clinical settings. His work therefore 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.
Dr Zucker heads up the comorbidity and late effects workstream of the Comprehensive Patient Records Project (CPR). This work aims to identify how pre-existing health conditions impact on outcomes in the 20 most common cancer and how cancer and its treatment impacts the long term health of patients. The research focusses on the analysis of large volumes of routinely collected health data including a linked dataset combining both primary and secondary care data. Dr Zucker has a particular interest in artificial intelligence methods and uses both traditional statistical approaches and machine learning approaches. His previous work has focussed on hospital only data however the CPR project seeks to use similar approaches to linked primary and secondary care data.
Dr Zucker is 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 rolled out across the Yorkshire and Humber Region. Dr Zucker also provides support to a range of other interdisciplinary projects across the university and in his role as NIHR clinical lecturer provides integrated data science and clinical input to several healthcare artificial intelligence researchers in the computer sciences department. Projects include automated image analytics for the diagnosis of Covid-19 from chest x-rays, automated reporting of cardiac MRI, process mining healthcare data, the development of interactive clinical outcomes dashboards, BRCA and breast cancer outcomes and health geography projects.
- BSc (Hons)
- Fellow of the Faculty of Clinical Informatics
- Member of the Royal College of Physicians
Dr Zucker is involved in a range of educational activities across the university. He has been involved in the teaching of undergraduate medicals students since 2012 and has provided both formal and informal teaching in clinical medicine. His work with undergraduate medical students now predominantly focusses on Oncology related teaching. Dr Zucker also acts as a PhD supervisor, MSc supervisor and LIDA data science intern supervisor. Dr Zucker Contributes 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)
Dr Zucker also increasingly delivers focussed teaching to clinical academics on data science with a particular focus on best practice approaches to coding.
Research groups and institutes
- Leeds Institute of Medical Research at St James's