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TabulaTime: Novel multimodal deep learning for Acute Coronary Syndrome prediction through environmental and clinical data integration

Lookup NU author(s): Dr Stephen WhiteORCiD

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Publication metadata

Author(s): Zhang X, Han L, Hassan S, Kalra P, Ritchie J, Diver C, Shorley J, White SJ

Publication type: Article

Publication status: Published

Journal: Artificial Intelligence in Medicine

Year: 2026

Volume: 176

Print publication date: 01/06/2026

Online publication date: 10/03/2026

Acceptance date: 02/03/2026

Date deposited: 19/03/2026

ISSN (print): 0933-3657

ISSN (electronic): 1873-2860

Publisher: Elsevier BV

URL: https://doi.org/10.1016/j.artmed.2026.103395

DOI: 10.1016/j.artmed.2026.103395

Data Access Statement: The data that support the findings of this study are not openly available due to the sensitive nature of the clinical data used in this study–sourced from the Myocardial Ischaemia National Audit Project (MINAP). These data are subject to strict data governance, patient confidentiality agreements, and institutional ethical approvals, which prohibit public release of individual-level health information, even in anonymised form.


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Funding

Funder referenceFunder name
British Heart Foundation Doug Gurr Cardiovascular Catalyst Award (BHF-CC/22/250021)
Engineering and Physical Sciences Research Council (EPSRC), UK (EP/X013707/1)

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