Kieran Zucker

Clinical Lecturer

University of Leeds

United Kingdom

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About

Dr. Kieran Zucker is a Clinical Lecturer at the University of Leeds, UK. His research interests encompass the application of artificial intelligence in healthcare, cancer survivorship, and the evaluation of therapeutic approaches for elderly patients. Dr. Zucker has contributed to several recent articles, focusing on topics such as the accuracy of clinical coding in cancer survival related to diabetes, machine learning methods for cancer detection, and the quality of life for cancer survivors.

Articles (10)

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2025

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2025

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2025

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2024

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2024

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2024

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2024

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2024

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2024

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2023

Collaborators (6)

Oliver Todd

NIHR Academic Clinical Lecturer / ST7 in Geriatric & Internal Medicine

University of Leeds

UNITED KINGDOM

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James van Oppen

University of Leicester

UNITED KINGDOM

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Ruth Evans

Lecturer in Health Informatics and Data Science

University of Leeds

UNITED KINGDOM

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Ciarán D. McInerney

University of Sheffield

UNITED KINGDOM

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Amanda Fitzpatrick

Clinical Senior Lecturer

King's College London

UNITED KINGDOM

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Mark Baxter

Academic, SCREDS Clinical Lecturer (Teaching and Scholarship)

University of Dundee

UNITED KINGDOM

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Kieran Zucker

Research Interests

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Articles (10)

Why NHS hospital co-morbidity research may be wrong: how clinical coding fails to identify the impact of diabetes mellitus on cancer survival

Multiple Instance Learning for the Detection of Lymph Node and Omental Metastases in Carcinoma of the Ovaries, Fallopian Tubes and Peritoneum

A comprehensive evaluation of histopathology foundation models for ovarian cancer subtype classification.

BMScope: A scoping review to chart the evolving clinical study landscape in brain and leptomeningeal metastasis

UK national observational cohort study investigating Tolerance of Anti-cancer Systemic Therapy in the Elderly: the TOASTIE study

Quality of life, healthcare usage and finances of UK cancer survivors five years post-diagnosis: a matched controlled study.

A United Kingdom prospective, multicentre, observational cohort study investigating tolerance of anti-cancer systemic therapy in the elderly: The TOASTIE study.

Evaluation of machine learning methods for the retrospective detection of ovarian cancer recurrences from chemotherapy data

Multi-centre benchmarking of deep learning models for COVID-19 detection in chest x-rays

New Horizons in artificial intelligence in the healthcare of older people.

Collaborators (6)

Oliver Todd

James van Oppen

Ruth Evans

Ciarán D. McInerney

Amanda Fitzpatrick

Mark Baxter

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