Sumeet Hindocha

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Clinical Lecturer

University College London

United Kingdom

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About

Dr. Sumeet Hindocha is a Clinical Lecturer at University College London, UK. His research interests encompass digital oncology, machine learning applications in cancer treatment, and radiomics, as highlighted in his recent publications such as the analysis of acute diarrhoea in rectal cancer chemoradiotherapy and innovations in artificial intelligence for radiotherapy. Dr. Hindocha is dedicated to advancing the understanding of non-small cell lung cancer and the integration of technology in clinical practice.

Recent Grants

Grant: Open

Temporal, Multi modal Deep Learning for Radiotherapy Toxicity and Outcome Prediction in Non Small Cell Lung Cancer

Open Date: 2025-01-01

Close Date: 2027-01-01

Grant: Close

Enriching the OCTAPUS-AI dataset with radiotherapy, tumour biomarkers and immunotherapy data

Open Date: 2024-06-01

Close Date: 2025-05-01

Grant: Close

CRUK RadNet City of London Radiation Research Unit NHS Staff/Oncologist in Residence Award

Open Date: 2023-11-01

Close Date: 2025-06-01

Grant: Close

Developing prognostication models for recurrence/survival following radiotherapy for NSCLC

Open Date: 2023-04-01

Close Date: 2023-11-01

Grant: Close

A radiomic classifier to distinguish causes of pneumonitis in NSCLC patients in the COVID-19 era

Open Date: 2020-04-01

Close Date: 2021-04-01

Articles (10)

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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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2023

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2023

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2023

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2023

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2022

Collaborators (7)

Mitchell Chen

Clinical Lecturer

Imperial College London

UNITED KINGDOM

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Zhuoyan Shen

University College London

UNITED KINGDOM

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Marco A. Calzado

Associate Professor

Universidad de Córdoba

SPAIN

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Nicholas West

University of Leeds School of Medicine

UNITED KINGDOM

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Douglas Brand

University College London

UNITED KINGDOM

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Bhupinder Sharma

Senior Lecturer & Honorary Faculty

Institute of Cancer Research

UNITED KINGDOM

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Andre Lopes

UNITED KINGDOM

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Sumeet Hindocha

Research Interests

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About

Recent Grants

Articles (10)

Predicting acute diarrhoea in rectal cancer chemoradiotherapy: Secondary analysis of the phase III ARISTOTLE trial

In the Nexus of Transformation: Innovations, Challenges and the Future of Digital Oncology

Validated machine learning tools to distinguish immune checkpoint inhibitor, radiotherapy, COVID-19 and other infective pneumonitis

Deep representation learning of tissue metabolome and computed tomography annotates NSCLC classification and prognosis

Contrast Clearance Analysis (CCA) to Assess Viable Tumour following Stereotactic Radiosurgery (SRS) to Brain Metastasis in Non-Small Cell Lung Cancer (NSCLC)

Non-contrast CT synthesis using patch-based cycle-consistent generative adversarial network (Cycle-GAN) for radiomics and deep learning in the era of COVID-19

The lung cancers: staging and response, CT, 18F-FDG PET/CT, MRI, DWI. Review and new perspectives

Future Proofing the Clinical Oncology Workforce

Artificial Intelligence for Radiotherapy Auto-Contouring: Current Use, Perceptions of and Barriers to Implementation

Gross tumour volume radiomics for prognostication of recurrence & death following radical radiotherapy for NSCLC

Collaborators (7)

Mitchell Chen

Zhuoyan Shen

Marco A. Calzado

Nicholas West

Douglas Brand

Bhupinder Sharma

Andre Lopes

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