Usman Jaffer

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Visiting Associate Professor

Anglia Ruskin University

United Kingdom

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Dr. Usman Jaffer is a Visiting Associate Professor at Anglia Ruskin University in the United Kingdom. His research focuses on the application of machine learning in healthcare, particularly in the diagnosis and management of peripheral arterial disease and related conditions. He has contributed to various scholarly articles, including studies on temporal artery ultrasound for giant cell arteritis and the effectiveness of communities of practice in healthcare.

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Diagnostic tools to establish the presence and severity of peripheral arterial disease in people with diabetes

Open Date: 2021-09-01

Close Date: 2024-08-31

Articles (10)

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2024

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2023

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2023

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2023

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2022

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2022

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2022

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2022

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2021

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2021

Collaborators (4)

Joseph J Boyle

Clinical Reader in Molecular Vascular Pathology

Imperial College London

UNITED KINGDOM

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Hussein Elghazaly

Imperial College London

UNITED KINGDOM

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Nicolas Peters

Imperial College London

UNITED KINGDOM

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John Norrie

Professor and Director

University of Edinburgh

UNITED KINGDOM

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Usman Jaffer

Research Interests

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About

Recent Grants

Articles (10)

Halo sign on temporal artery ultrasound versus temporal artery biopsy for giant cell arteritis.

Evaluating the prognostic performance of bedside tests used for peripheral arterial disease diagnosis in the prediction of diabetic foot ulcer healing

The aims and effectiveness of communities of practice in healthcare: A systematic review.

Tensor decomposition and machine learning for the detection of arteriovenous fistula stenosis: An initial evaluation.

Study protocol for a multicentre comparative diagnostic accuracy study of tools to establish the presence and severity of peripheral arterial disease in people with diabetes mellitus: the DM PAD study

Peripheral blood mononuclear cell gene expression and cytokine profiling in patients with intermittent claudication who exhibit exercise induced acute renal injury

A Pilot Study of Heart Rate Variability Synchrony as a Marker of Intraoperative Surgical Teamwork and Its Correlation to the Length of Procedure.

Machine learning-based classification of arterial spectral waveforms for the diagnosis of peripheral artery disease in the context of diabetes: A proof-of-concept study.

Factors Affecting Engagement in Web-Based Health Care Patient Information: Narrative Review of the Literature

Harnessing Machine Learning to Personalize Web-Based Health Care Content.

Collaborators (4)

Joseph J Boyle

Hussein Elghazaly

Nicolas Peters

John Norrie

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