Hugh Harvey
Hugh Harvey
Hardian Health
Verified email at - Homepage
Cited by
Cited by
Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension
X Liu, SC Rivera, D Moher, MJ Calvert, AK Denniston, H Ashrafian, ...
The Lancet Digital Health 2 (10), e537-e548, 2020
Preparing medical imaging data for machine learning
MJ Willemink, WA Koszek, C Hardell, J Wu, D Fleischmann, H Harvey, ...
Radiology 295 (1), 4-15, 2020
Artificial intelligence versus clinicians: systematic review of design, reporting standards, and claims of deep learning studies
M Nagendran, Y Chen, CA Lovejoy, AC Gordon, M Komorowski, ...
bmj 368, 2020
Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension
SC Rivera, X Liu, AW Chan, AK Denniston, MJ Calvert, H Ashrafian, ...
The Lancet Digital Health 2 (10), e549-e560, 2020
Reporting guideline for the early stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI
B Vasey, M Nagendran, B Campbell, DA Clifton, GS Collins, S Denaxas, ...
bmj 377, 2022
Artificial intelligence in diagnostic imaging: impact on the radiography profession
M Hardy, H Harvey
The British journal of radiology 93 (1108), 20190840, 2020
Lifecycle regulation of artificial intelligence–and machine learning–based software devices in medicine
TJ Hwang, AS Kesselheim, KN Vokinger
Jama 322 (23), 2285-2286, 2019
To buy or not to buy—evaluating commercial AI solutions in radiology (the ECLAIR guidelines)
P Omoumi, A Ducarouge, A Tournier, H Harvey, CE Kahn, ...
European radiology 31, 3786-3796, 2021
Regulatory frameworks for development and evaluation of artificial intelligence–based diagnostic imaging algorithms: summary and recommendations
DB Larson, H Harvey, DL Rubin, N Irani, RT Justin, CP Langlotz
Journal of the American College of Radiology 18 (3), 413-424, 2021
Large language model AI chatbots require approval as medical devices
S Gilbert, H Harvey, T Melvin, E Vollebregt, P Wicks
Nature Medicine 29 (10), 2396-2398, 2023
High-Resolution Mammogram Synthesis using Progressive Generative Adversarial Networks.
D Korkinof, T Rijken, M O’Neill, J Yearsley, H Harvey, B Glocker
URL http://arxiv. org/abs/1807.03401, 2018
Machine learning “red dot”: open-source, cloud, deep convolutional neural networks in chest radiograph binary normality classification
EJ Yates, LC Yates, H Harvey
Clinical radiology 73 (9), 827-831, 2018
A standardised approach for preparing imaging data for machine learning tasks in radiology
H Harvey, B Glocker
Artificial intelligence in medical imaging: opportunities, applications and …, 2019
SPIRIT-AI and CONSORT-AI Working Group; SPIRIT-AI and CONSORT-AI Steering Group; SPIRIT-AI and CONSORT-AI Consensus Group. Guidelines for clinical trial protocols for …
S Cruz Rivera, X Liu, AW Chan, AK Denniston, MJ Calvert
Nat Med 26 (9), 1351-1363, 2020
Best practices for authors of healthcare-related artificial intelligence manuscripts
LWJK Sujay Kakarmath, Andre Esteva, Rima Arnaout, Hugh Harvey, Santosh Kumar ...
NPJ Digital Medicine 3 (134), 2020
The role of deep learning in breast screening
H Harvey, E Karpati, G Khara, D Korkinof, A Ng, C Austin, T Rijken, ...
Current Breast Cancer Reports 11, 17-22, 2019
TRIPOD+ AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods
GS Collins, KGM Moons, P Dhiman, RD Riley, AL Beam, B Van Calster, ...
bmj 385, 2024
Why AI will not replace radiologists
H Harvey
Towards Data Science. Retrieved June 10, 2021, 2018
Volumetry of the dominant intraprostatic tumour lesion: intersequence and interobserver differences on multiparametric MRI
H Harvey, MR Orton, VA Morgan, C Parker, D Dearnaley, C Fisher, ...
The British journal of radiology 90 (1071), 20160416, 2017
The role of imaging in the diagnosis of primary prostate cancer
H Harvey, NM deSouza
Journal of clinical urology 9 (2_suppl), 11-17, 2016
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