Syed Ali Khurram

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Professor and Consultant Pathologist

University of Sheffield

United Kingdom

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About

Syed Ali Khurram is a Professor and Consultant Pathologist at the University of Sheffield, UK. His research focuses on the application of artificial intelligence in oral pathology, particularly in the diagnosis and prognosis of salivary gland tumours, odontogenic cysts, and oral epithelial dysplasia. Recent publications include studies on histopathological variability, interobserver differences among pathologists, and the tumorigenesis of pleomorphic adenomas. Professor Khurram's work aims to enhance diagnostic accuracy and understanding of oral pathologies through innovative methodologies.

Recent Grants

Grant: Close

ANTICIPATE- Using AI for automated detection & grading of oral dysplasia

Open Date: 2020-10-01

Close Date: 2023-10-01

Grant: Close

Epithelial-fibroblast cross-talk in metastatic intranodal oral squamous cell carcinoma- Is it the hallmark of aggressive disease?

Open Date: 2013-02-01

Close Date:

Articles (19)

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2021

Collaborators (12)

Saman Warnakulasuriya

Professor

King’s College London

UNITED KINGDOM

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D. W. Lambert

UNITED KINGDOM

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Neda Azarmehr

University of West London

UNITED KINGDOM

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Keith Hunter

Professor of Head and Neck Pathology

University of Liverpool

UNITED KINGDOM

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Hanya Mahmood

University of Sheffield

UNITED KINGDOM

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James Dolezal

Assistant Professor

Geisinger Medical Center

UNITED STATES

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Susan Heavey

University College London

UNITED KINGDOM

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Lynne Bingle

UNITED KINGDOM

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Hassan Aqeel Khan

Aston University

UNITED KINGDOM

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Omar Kujan

University of Western Australia

AUSTRALIA

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Stefano Fedele

Professor of Oral Medicine

University College London

UNITED KINGDOM

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Georgina Al-Badri

University College London

UNITED KINGDOM

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Syed Ali Khurram

Research Interests

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About

Recent Grants

Articles (19)

Exploring the feasibility of AI-based analysis of histopathological variability in salivary gland tumours

Exploring the Role of Artificial Intelligence in Oral Pathology: Diagnostic and Prognostic Implications

The use of artificial intelligence in the diagnosis of odontogenic cysts and tumors

A head‐to‐head comparison of four grading systems for oral epithelial dysplasia

Understanding interobserver variability of pathologists to improve oral epithelial dysplasia grading

Pleomorphic adenoma and carcinoma ex‐pleomorphic adenoma tumorigenesis: A proteomic analysis

Demystifying oral epithelial dysplasia: a histological guide

Prognostic importance of mitosis quantification and PHH3 expression in oral epithelial dysplasia

Spatial transcriptomic interrogation of the tumour-stroma boundary in a 3D engineered model of ameloblastoma

A digital score of peri‐epithelial lymphocytic activity predicts malignant transformation in oral epithelial dysplasia

Machine learning for detection and classification of oral potentially malignant disorders: A conceptual review

Machine learning concepts applied to oral pathology and oral medicine: A convolutional neural networks' approach

A little bit of LOGIC goes a long way: Multidisciplinary management of LOGIC Syndrome‐associated oral manifestations

Transcriptionally active HPV in OPMD and OSCC: A systematic review following the CAP/ASCO guidelines

Keratoameloblastoma: A Report of Seven New Cases and Review of Literature

NUT Carcinoma Arising from the Parotid Gland: A Case Report and Review of the Literature

Oral cancer stem cells drive tumourigenesis through activation of stromal fibroblasts

Pakistan Oral Cancer Collaborative: analyzing barriers and obstacles to oral cancer diagnosis, treatment, and prevention in Pakistan

Automated feature detection in dental periapical radiographs by using deep learning

Collaborators (12)

Saman Warnakulasuriya

D. W. Lambert

Neda Azarmehr

Keith Hunter

Hanya Mahmood

James Dolezal

Susan Heavey

Lynne Bingle

Hassan Aqeel Khan

Omar Kujan

Stefano Fedele

Georgina Al-Badri

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