Profile

Dr Zucker completed his BSc in Medical Sciences with Molecular Medicine at University College London (UCL) in 2009 undertaking research in 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 where he works on a number of projects including cancer outcome prediction, computer vision, natural language processing, data visualisation and process mining. Dr Zucker is also a Fellow of the Faculty of Clinical Informatics where he has co-founded the Early Career Group. He also sits on the Faculty’s Artificial Intelligence Specialist Interest Group and the Education and Training Subcommittee.

Responsibilities

• Clinical Researcher
• Center for Doctoral Training In Medical Artificial Intelligence Supervisor
• LIDA Data Science Intern Supervisor

Research interests

Dr Zucker heads up the comorbidity and late effects workstream of the Macmillan funded Comprehensive Patient Records Project. This work aims to identify how pre-existing health conditions impact outcomes in the 20 most common cancer and how cancer and its treatment impact the long term health of patients. The research focuses 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 in analytical approaches.

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. 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.