Dr Xiaoxuan Liu MBChB, PhD

Xiaoxuan Liu

Institute of Inflammation and Ageing
Clinical Researcher in Artificial Intelligence and Digital Health Technologies
Specialty Registrar in Ophthalmology

Contact details

Telephone
+44 (0)121 371 8132
Email
x.liu.8@bham.ac.uk
Twitter
@DrXiaoLiu
Address
Institute of Inflammation and Ageing
University of Birmingham
Edgbaston
Birmingham
B15 2TT
UK

Dr Xiao Liu is a clinical researcher and specialty registrar in ophthalmology at the Institute of Inflammation and Ageing, University of Birmingham and University Hospitals Birmingham NHS Foundation Trust.

Dr Liu’s work sits at the intersection of artificial intelligence and digital health technologies and health policy and regulation. Her research aims to ensure AI and digital health technologies are safe, effective and equitably. She co-leads the SPIRIT-AI and CONSORT-AI initiative, international standards for reporting of AI clinical trials, and the STANDING Together project, which aims to tackle bias in health datasets to ensure AI benefits all.

Her PhD was around validation of an optical coherence tomography based image analysis technique for detecting and quantifying inflammation in the eye, under the supervision of Professor Alastair Denniston, Professor David Moore and Professor Pearse Keane.

She has a number of advisory roles on AI in healthcare including the MHRA, NICE (academic partner on the Evidence Standards for Digital Health Technologies) WHO/ITU Working Group for AI in Health and as a member of the NHS AI Lab Evaluation Advisory Group for the AI in Health and Care Award. Dr Liu is also an honorary research fellow at the Alan Turing Institute, Health Data Research UK and the Artificial Intelligence hub at Moorfields Eye Hospital Reading Centre.

Dr Xiao Liu MBChB PhD

Qualifications

  • PhD, University of Birmingham, 2017-2021
  • MBChB, University of Birmingham, 2010-2015

Biography

Dr Liu studied medicine at the University of Birmingham College of Medical and Dental Sciences and graduated in in 2015. She completed her foundation programme as a junior doctor at University Hospitals Birmingham NHS Foundation Trust and Sandwell and West Birmingham Hospitals NHS Trust. Dr Liu completed her PhD at the University of Birmingham between 2017-2021. She commenced specialty training in ophthalmology in the West Midlands deanery in 2021 and splits her time between clinical training and research as a clinical research fellow at University Hospitals Birmingham NHS Foundation Trust.

Research

Dr Liu’s research interests include:

  1. Evidence standards for AI in healthcare
  2. Regulatory considerations for AI in health care
  3. Building health systems and enabling health professionals to effectively implement AI health technologies
  4. Health Data Research in Ophthalmology
  5. Ophthalmic imaging and eye imaging-based biomarkers

Other activities

  • Clinical research fellow at University Hospitals Birmingham NHS Foundation Trust
  • Honorary clinical research fellow at Moorfields Eye Hospital, London
  • Health Data Research UK Early Career Researchers Committee

Publications

Liu, X., Cruz Rivera, S., Moher, D. et al. Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension. Nat Med 26, 1364–1374 (2020).

Cruz Rivera, S., Liu, X., Chan, A. et al. Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension. Nat Med 26, 1351–1363 (2020).

Liu X, Cruz Rivera S, Moher D, et al. Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension. The Lancet Digital Health. Published online September 9, 2020.

Cruz Rivera S, Liu X, Chan A-W, et al. Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension. The Lancet Digital Health. Published online September 9, 2020.

Liu X, Rivera SC, Moher D, Calvert MJ, Denniston AK. Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI Extension. BMJ. 2020;370.

Rivera SC, Liu X, Chan A-W, Denniston AK, Calvert MJ. Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI Extension. BMJ. 2020;370.

McNally TW, Liu X, Beese S, Keane PA, Moore DJ, Denniston AK. Instrument-based tests for quantifying aqueous humour protein levels in uveitis: a systematic review protocol. Syst Rev. 2019;8(1):287.

Liu X, Kale AU, Capewell N, et al. Optical coherence tomography (OCT) in unconscious and systemically unwell patients using a mobile OCT device: a pilot study. BMJ Open. 2019;9(11):e030882.

Liu X, Faes L, Kale AU, et al. A comparison of deep learning performance against health-care professionals in detecting diseases from medical imaging: a systematic review and meta-analysis. The Lancet Digital Health. September 2019. doi:10.1016/S2589-7500(19)30123-2

CONSORT-AI and SPIRIT-AI Steering Group. Reporting guidelines for clinical trials evaluating artificial intelligence interventions are needed. Nat Med. September 2019. doi:10.1038/s41591-019-0603-3

Liu X, Faes L, Calvert MJ, Denniston AK, CONSORT/SPIRIT-AI Extension Group. Extension of the CONSORT and SPIRIT statements. Lancet. September 2019. doi:10.1016/S0140-6736(19)31819-7

Faes L, Wagner SK, Fu DJ, et al. Automated deep learning design for medical image classification by health-care professionals with no coding experience: a feasibility study. The Lancet Digital Health. 2019;1(5):e232-e242.

Liu X, Solebo AL, Faes L, et al. Instrument-based Tests for Measuring Anterior Chamber Cells in Uveitis: A Systematic Review. Ocular Immunology and Inflammation. 2019:1-12. doi:10.1080/09273948.2019.1640883

Liu X, Kelly SR, Montesano G, et al. Evaluating the Impact of Uveitis on Visual Field Progression Using Large Scale Real-World Data. Am J Ophthalmol. June 2019. doi:10.1016/j.ajo.2019.06.004

Ometto G, Moghul I, Montesano G, et al. ReLayer: a Free, Online Tool for Extracting Retinal Thickness From Cross-Platform OCT Images. Transl Vis Sci Technol. 2019;8(3):25.

Bailie HN, Liu X, Bruynseels A, Denniston AK, Shah P, Sii F. The Uveitis Patient Passport: A Self-Care Tool. Ocul Immunol Inflamm 2019:1–6. doi:10.1080/09273948.2019.1569240.

Liu X, Solebo AL, Keane PA, Moore DJ, Denniston AK. Instrument-based tests for measuring anterior chamber cells in uveitis: a systematic review protocol. Syst Rev 2019;8:30. doi:10.1186/s13643-019-0946-3.

Liu X, Keane PA, Denniston AK. Time to regenerate: the doctor in the age of artificial intelligence. J R Soc Med. 2018;111:113–6. Available from: http://journals.sagepub.com/doi/10.1177/0141076818762648.

Damato EM, Dawson S, Liu X, Mukherjee C, Horsburgh J, Denniston AK, et al. A retrospective cohort study of patients treated with anti-tuberculous therapy for presumed ocular tuberculosis. J Ophthalmic Inflamm Infect. 2017;7:23. Available from: http://www.ncbi.nlm.nih.gov/pubmed/29204932

Montesano G, Way CM, Ometto G, Ibrahim H, Jones PR, Carmichael R, et al. Optimizing OCT acquisition parameters for assessments of vitreous haze for application in uveitis. Sci Rep. Nature Publishing Group; 2018. Available from: http://www.nature.com/articles/s41598-018-20092-y

Liu X, Sii F, Horsburgh J, Shah P. Anuric acute kidney injury due to low dose oral acetazolamide with hypercrystalluria. Clin Experiment Ophthalmol. Wiley/Blackwell (10.1111); 2017;45:927–9. Available from: http://doi.wiley.com/10.1111/ceo.12980

Liu X, Calvert PA, Arif S, Keane PA, Denniston AK. Patent foramen ovale presenting as visual loss. JRSM open. SAGE Publications; 2016;8:2054270416669302. Available from: http://www.ncbi.nlm.nih.gov/pubmed/28203381