Follow
Xiao Liu
Xiao Liu
University Hospitals Birmingham, University of Birmingham, UK
Verified email at bham.ac.uk
Title
Cited by
Cited by
Year
A comparison of deep learning performance against health-care professionals in detecting diseases from medical imaging: a systematic review and meta-analysis
X Liu, L Faes, AU Kale, SK Wagner, DJ Fu, A Bruynseels, T Mahendiran, ...
The lancet digital health 1 (6), e271-e297, 2019
14462019
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
7382020
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
6302020
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
2602022
Automated deep learning design for medical image classification by health-care professionals with no coding experience: a feasibility study
L Faes, SK Wagner, DJ Fu, X Liu, E Korot, JR Ledsam, T Back, R Chopra, ...
The Lancet Digital Health 1 (5), e232-e242, 2019
2592019
SPIRIT-AI and CONSORT-AI Working Group. Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension
X Liu, S Cruz Rivera, D Moher, MJ Calvert, AK Denniston
Nat Med 26 (9), 1364-1374, 2020
2212020
A global review of publicly available datasets for ophthalmological imaging: barriers to access, usability, and generalisability
SM Khan, X Liu, S Nath, E Korot, L Faes, SK Wagner, PA Keane, ...
The Lancet Digital Health 3 (1), e51-e66, 2021
2202021
Developing specific reporting guidelines for diagnostic accuracy studies assessing AI interventions: The STARD-AI Steering Group
V Sounderajah, H Ashrafian, R Aggarwal, J De Fauw, AK Denniston, ...
Nature medicine 26 (6), 807-808, 2020
1952020
Health data poverty: an assailable barrier to equitable digital health care
H Ibrahim, X Liu, N Zariffa, AD Morris, AK Denniston
The Lancet Digital Health 3 (4), e260-e265, 2021
1852021
Insights into systemic disease through retinal imaging-based oculomics
SK Wagner, DJ Fu, L Faes, X Liu, J Huemer, H Khalid, D Ferraz, E Korot, ...
Translational vision science & technology 9 (2), 6-6, 2020
1532020
The medical algorithmic audit
X Liu, B Glocker, MM McCradden, M Ghassemi, AK Denniston, ...
The Lancet Digital Health 4 (5), e384-e397, 2022
1412022
Developing a reporting guideline for artificial intelligence-centred diagnostic test accuracy studies: the STARD-AI protocol
V Sounderajah, H Ashrafian, RM Golub, S Shetty, J De Fauw, L Hooft, ...
BMJ open 11 (6), e047709, 2021
1402021
A clinician's guide to artificial intelligence: how to critically appraise machine learning studies
L Faes, X Liu, SK Wagner, DJ Fu, K Balaskas, DA Sim, LM Bachmann, ...
Translational vision science & technology 9 (2), 7-7, 2020
1362020
Characteristics of publicly available skin cancer image datasets: a systematic review
D Wen, SM Khan, AJ Xu, H Ibrahim, L Smith, J Caballero, L Zepeda, ...
The Lancet Digital Health 4 (1), e64-e74, 2022
1302022
SPIRIT-AI and CONSORT-AI Working Group. Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI Extension
S Cruz Rivera, X Liu, AW Chan, AK Denniston, MJ Calvert
Lancet Digit Health 2 (10), e549-e560, 2020
1282020
Code-free deep learning for multi-modality medical image classification
E Korot, Z Guan, D Ferraz, SK Wagner, G Zhang, X Liu, L Faes, ...
Nature Machine Intelligence 3 (4), 288-298, 2021
1272021
DECIDE-AI: new reporting guidelines to bridge the development-to-implementation gap in clinical artificial intelligence
Nature Medicine 27 (2), 186-187, 2021
1232021
Predicting sex from retinal fundus photographs using automated deep learning
E Korot, N Pontikos, X Liu, SK Wagner, L Faes, J Huemer, K Balaskas, ...
Scientific reports 11 (1), 10286, 2021
952021
A quality assessment tool for artificial intelligence-centered diagnostic test accuracy studies: QUADAS-AI
V Sounderajah, H Ashrafian, S Rose, NH Shah, M Ghassemi, R Golub, ...
Nature medicine 27 (10), 1663-1665, 2021
922021
Reporting guidelines for clinical trials evaluating artificial intelligence interventions are needed
Nature Medicine 25 (10), 1467-1468, 2019
822019
The system can't perform the operation now. Try again later.
Articles 1–20