Professor Alastair Denniston MA MRCP FRCOphth PhD

Image of Professor Alastair Denniston

Department of Applied Health Sciences
Chair of Regulatory Science and Innovation
Hon Consultant Ophthalmologist

Contact details

Telephone
+44 (0)121 371 6905
Email
a.denniston@bham.ac.uk
View my research portal
Address
Institute of Applied Health Research
College of Medical and Dental Sciences
University of Birmingham
Edgbaston
Birmingham
B15 2TT
UK

Prof Alastair Denniston is Professor of Regulatory Science and Innovation at the University of Birmingham and Honorary Consultant Ophthalmologist at University Hospitals Birmingham NHSFT. He is a leader in the field of Artificial Intelligence (AI) and Digital Health Technologies.

Prof Denniston and Dr Xiaoxuan Liu co-lead the AI & Digital Health Group, a research and policy group focused on responsible innovation of AI health technologies. The group’s work seeks to ensure AI technologies are safe, effective and equitable, and benefits patients and society. The group’s work includes:

Improving scientific standards - developing internationally adopted reporting guidelines for clinical trials of AI health technologies: SPIRIT-AI and CONSORT-AI; and contributing to other AI reporting standards including TRIPOD+AI, STARD-AI, and DECIDE-AI.

Improving evidence - building evidence standards for digital health technologies for NICE (DHT-ESF), in collaboration with Imperial College London and the Alan Turing Institute.

Improving safety - developing tools for assessing safety of AI-enabled medical devices: the medical algorithmic audit, and through working directly with medical device regulators such as the MHRA.

Improving diversity and representation within the data used in AI - tackling bias in health datasets to mitigate AI-driven health inequalities through STANDING Together.

The group works in collaboration with academic, industry and policy institutions around the world, bringing diverse and interdisciplinary teams together to build best practices that can be translated internationally.

Qualifications

  • FRCOphth, Royal College of Ophthalmologists 2010
  • PhD, University of Birmingham, 2010
  • MRCOphth, Royal College of Ophthalmologists, 2003
  • MRCP, Royal College of Physicians, 2000
  • MA, University of Cambridge 2000                    
  • MB BChir, University of Cambridge 1997           
  • BA Medical Sciences Tripos, University of Cambridge 1995 

Biography

Alastair Denniston graduated as Senior Whitby Scholar from Downing College, Cambridge in 1995 with a BA in Medical Sciences. He undertook general medical training first in Cambridge and then Birmingham gaining Membership of the Royal College of Physicians in 2000. He then trained in Ophthalmology becoming Clinical Lecturer at the University of Birmingham in 2005, before being awarded an MRC Clinical Research Training Fellowship in 2006. His PhD in Dendritic Cell Regulation in the Ocular Microenvironment was completed in 2009. He became a Fellow of the Royal College of Ophthalmologists in 2010, and was appointed Consultant at University Hospitals Birmingham in 2012 and promoted to Hon Professor at University of Birmingham in 2017, where he leads the Birmingham AI & Digital Health Group with Dr Xiaoxuan Liu. In 2019 he founded INSIGHT, the HDRUK Data Hub for Eye Health, with Professor Pearse Keane; INSIGHT is now the world’s largest ophthalmic imaging bioresource. In 2023 he was appointed NIHR Senior Investigator.

Alastair’s leadership roles in AI and responsible innovation include: Vice-Chair of the WHO-ITU Group on Evaluation of AI in Health; Member of the Regulatory Horizons Council to the UK Government; Advisor on AI to MHRA, National Screening Committee, and other national bodies; System Lead for AI Diagnostics to NHS England.

Teaching

Teaching Programmes 

Postgraduate supervision

Alastair supervises doctoral research students in the evaluation and regulation of AI & digital health technologies, addressing issues of safety, effectiveness and equity as part of a responsible approach to AI innovation.

If you are interesting in studying any of these subject areas please contact Alastair on the contact details above.

For a full list of available Doctoral Research opportunities, please visit our Doctoral Research programme listings.   

Research

Research themes

The group’s work seeks to ensure AI technologies are safe, effective and equitable, and benefits patients and society. 

Research projects

  • Improving scientific standards 
  • Improving evidence 
    • Creating the evidence standards for digital health technologies for NICE (DHT-ESF), in collaboration with Imperial College London and the Alan Turing Institute.
  • Improving safety 
    • Developing tools for assessing safety of AI-enabled medical devices: the medical algorithmic audit
    • Leading global surveys of safety reports of AI-enabled medical devices
    • Working directly with medical device regulators such as the MHRA.
  • Improving diversity and representation within the data used in AI
    • Tackling bias in health datasets to mitigate AI-driven health inequalities through STANDING Together.
  • Emerging challenges and opportunities
    • Exploring bias within Large Language Models
    • Using Target Product Profiles to accelerate AI innovation that meets the needs of the NHS 

Other activities

Publications

Selected publications

Ganapathi S, Palmer J, Alderman JE, Calvert M, Espinoza C, Gath J, Ghassemi M, Heller K, Mckay F, Karthikesalingam A, Kuku S, Mackintosh M, Manohar S, Mateen BA, Matin R, McCradden M, Oakden-Rayner L, Ordish J, Pearson R, Pfohl SR, Rostamzadeh N, Sapey E, Sebire N, Sounderajah V, Summers C, Treanor D, Denniston AK, Liu X. Tackling bias in AI health datasets through the STANDING Together initiative. Nat Med. 2022 Nov;28(11):2232-2233. doi: 10.1038/s41591-022-01987-w. PMID: 36163296.

Regulatory Horizons Council. The regulation of AI as a medical device. 2022. https://www.gov.uk/government/publications/regulatory-horizons-council-the-regulation-of-artificial-intelligence-as-a-medical-device

Cruz Rivera S, Liu X, Hughes SE, Dunster H, Manna E, Denniston AK, Calvert MJ. Embedding patient-reported outcomes at the heart of artificial intelligence health-care technologies. Lancet Digit Health. 2023 Mar;5(3):e168-e173. doi: 10.1016/S2589-7500(22)00252-7. PMID: 36828609.

Cacciamani GE, Chu TN, Sanford DI, Abreu A, Duddalwar V, Oberai A, Kuo CJ, Liu X, Denniston AK, Vasey B, McCulloch P, Wolff RF, Mallett S, Mongan J, Kahn CE Jr, Sounderajah V, Darzi A, Dahm P, Moons KGM, Topol E, Collins GS, Moher D, Gill IS, Hung AJ. PRISMA AI reporting guidelines for systematic reviews and meta-analyses on AI in healthcare. Nat Med. 2023 Jan;29(1):14-15. doi: 10.1038/s41591-022-02139-w. PMID: 36646804.

Vasey B, Nagendran M, Campbell B, Clifton DA, Collins GS, Denaxas S, Denniston AK, Faes L, Geerts B, Ibrahim M, Liu X, Mateen BA, Mathur P, McCradden MD, Morgan L, Ordish J, Rogers C, Saria S, Ting DSW, Watkinson P, Weber W, Wheatstone P, McCulloch P; DECIDE-AI expert group. Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI. Nat Med. 2022 May;28(5):924-933. doi: 10.1038/s41591-022-01772-9. Epub 2022 May 18. PMID: 35585198.

Calvert MJ, Cruz Rivera S, Retzer A, Hughes SE, Campbell L, Molony-Oates B, Aiyegbusi OL, Stover AM, Wilson R, McMullan C, Anderson NE, Turner GM, Davies EH, Verdi R, Velikova G, Kamudoni P, Muslim S, Gheorghe A, O'Connor D, Liu X, Wu AW, Denniston AK. Patient reported outcome assessment must be inclusive and equitable. Nat Med. 2022 Jun;28(6):1120-1124. doi: 10.1038/s41591-022-01781-8. PMID: 35513530.

Liu X, Glocker B, McCradden MM, Ghassemi M, Denniston AK, Oakden-Rayner L. The medical algorithmic audit. Lancet Digit Health. 2022 May;4(5):e384-e397. doi: 10.1016/S2589-7500(22)00003-6. Epub 2022 Apr 5. Erratum in: Lancet Digit Health. 2022 Apr 21;: PMID: 35396183.

Unsworth H, Wolfram V, Dillon B, Salmon M, Greaves F, Liu X, MacDonald T, Denniston AK, Sounderajah V, Ashrafian H, Darzi A, Ashurst C, Holmes C, Weller A; NICE Artificial Intelligence Evidence Standards Working Group. Building an evidence standards framework for artificial intelligence-enabled digital health technologies. Lancet Digit Health. 2022 Apr;4(4):e216-e217. doi: 10.1016/S2589-7500(22)00030-9. PMID: 35337640.

Wagner SK, Hughes F, Cortina-Borja M, Pontikos N, Struyven R, Liu X, Montgomery H, Alexander DC, Topol E, Petersen SE, Balaskas K, Hindley J, Petzold A, Rahi JS, Denniston AK, Keane PA. AlzEye: longitudinal record-level linkage of ophthalmic imaging and hospital admissions of 353 157 patients in London, UK. BMJ Open. 2022 Mar 16;12(3):e058552. doi: 10.1136/bmjopen-2021-058552. PMID: 35296488; PMCID: PMC8928293.

Wen D, Khan SM, Ji Xu A, Ibrahim H, Smith L, Caballero J, Zepeda L, de Blas Perez C, Denniston AK, Liu X, Matin RN. Characteristics of publicly available skin cancer image datasets: a systematic review. Lancet Digit Health. 2022 Jan;4(1):e64-e74. doi: 10.1016/S2589-7500(21)00252-1. Epub 2021 Nov 9. PMID: 34772649.

Khan SM, Liu X, Nath S, Korot E, Faes L, Wagner SK, Keane PA, Sebire NJ, Burton MJ, Denniston AK. A global review of publicly available datasets for ophthalmological imaging: barriers to access, usability, and generalisability. Lancet Digit Health. 2021 Jan;3(1):e51-e66. doi: 10.1016/S2589-7500(20)30240-5. Epub 2020 Oct 1. Erratum in: Lancet Digit Health. 2021 Jan;3(1):e7. PMID: 33735069.

Cruz Rivera S, Liu X, Chan AW, Denniston AK, Calvert MJ; 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 interventions involving artificial intelligence: the SPIRIT-AI extension. Nat Med. 2020 Sep;26(9):1351-1363. doi: 10.1038/s41591-020-1037-7. Epub 2020 Sep 9. PMID: 32908284; PMCID: PMC7598944.

Liu X, Cruz Rivera S, Moher D, Calvert MJ, Denniston AK; SPIRIT-AI and CONSORT-AI Working Group. Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension. Nat Med. 2020 Sep;26(9):1364-1374. doi: 10.1038/s41591-020-1034-x. Epub 2020 Sep 9. PMID: 32908283; PMCID: PMC7598943.

Faes L, Liu X, Wagner SK, Fu DJ, Balaskas K, Sim DA, Bachmann LM, Keane PA, Denniston AK. A Clinician's Guide to Artificial Intelligence: How to Critically Appraise Machine Learning Studies. Transl Vis Sci Technol. 2020 Feb 12;9(2):7. doi: 10.1167/tvst.9.2.7. PMID: 32704413; PMCID: PMC7346877.

Liu X, Faes L, Kale AU, Wagner SK, Fu DJ, Bruynseels A, Mahendiran T, Moraes G, Shamdas M, Kern C, Ledsam JR, Schmid MK, Balaskas K, Topol EJ, Bachmann LM, Keane PA, Denniston AK. A comparison of deep learning performance against health-care professionals in detecting diseases from medical imaging: a systematic review and meta-analysis. Lancet Digit Health. 2019 Oct;1(6):e271-e297. doi: 10.1016/S2589-7500(19)30123-2. Epub 2019 Sep 25. Erratum in: Lancet Digit Health. 2019 Nov;1(7):e334. PMID: 33323251.

Denniston AK, Keane PA, Aojula A, Sinclair AJ, Mollan SP. The Ocular Glymphatic System and Idiopathic Intracranial Hypertension: Author Response to "Hypodense Holes and the Ocular Glymphatic System". Invest Ophthalmol Vis Sci. 2017 Feb 1;58(2):1134-1136. doi: 10.1167/iovs.17-21479. PubMed PMID: 28196227.

Blair J, Barry R, Moore DJ, Denniston AK. A comprehensive review of mTOR-inhibiting pharmacotherapy for the treatment of non-infectious uveitis. Curr Pharm Des. 2017 Jan 11. [Epub ahead of print] PubMed PMID: 28078989.

Chu CJ, Dick AD, Johnston RL, Yang YC, Denniston AK; UK Pseudophakic Macular Edema Study Group.. Cataract surgery in uveitis: a multicentre database study. Br J Ophthalmol. 2017 Jan 2. pii: bjophthalmol-2016-309047. doi 10.1136/bjophthalmol-2016-309047. [Epub ahead of print] PubMed PMID: 28043984.

Egan C, Zhu H, Lee A, Sim D, Mitry D, Bailey C, Johnston R, Chakravarthy U, Denniston A, Tufail A, Khan R, Mahmood S, Menon G, Akerele T, Downey L, McKibbin  M, Varma A, Lobo A, Wilkinson E, Fitt A, Brand C, Tsaloumas M, Mandal K, Kumar V, Matha S, Crabb D; UK AMD and DR EMR Users Group.. The United Kingdom Diabetic Retinopathy Electronic Medical Record Users Group, Report 1: baseline characteristics and visual acuity outcomes in eyes treated with intravitreal injections of ranibizumab for diabetic macular oedema. Br J Ophthalmol. 2017 Jan;101(1):75-80. doi: 10.1136/bjophthalmol-2016-309313. PubMed PMID: 27965262.

Denniston AK, Keane PA. "Black Holes" and the Ocular Glymphatic System: Author Response to "The Glymphatic System: A New Player in Ocular Diseases?" Invest Ophthalmol Vis Sci. 2016 Oct 1;57(13):5428. doi: 10.1167/iovs.16-20479. PubMed PMID: 27768787.

Williams GP, Nightingale P, Southworth S, Denniston AK, Tomlins PJ, Turner S,  Hamburger J, Bowman SJ, Curnow SJ, Rauz S. Conjunctival Neutrophils Predict Progressive Scarring in Ocular Mucous Membrane Pemphigoid. Invest Ophthalmol Vis  Sci. 2016 Oct 1;57(13):5457-5469. doi: 10.1167/iovs.16-19247. PubMed PMID: 27760272; PubMed Central PMCID: PMC5072540.

Ahnood D, Madhusudhan S, Tsaloumas MD, Waheed NK, Keane PA, Denniston AK. Punctate inner choroidopathy: A review. Surv Ophthalmol. 2017 Mar - Apr;62(2):113-126. doi: 10.1016/j.survophthal.2016.10.003. Review. PubMed PMID: 27751823.

Mollan SP, Keane PA, Denniston AK. The use of transdermal optical coherence tomography to image the superficial temporal arteries. Eye (Lond). 2017 Jan;31(1):157-160. doi: 10.1038/eye.2016.206. PubMed PMID: 27740619; PubMed Central PMCID: PMC5233932.

Lane M, Moult EM, Novais EA, Louzada RN, Cole ED, Lee B, Husvogt L, Keane PA, Denniston AK, Witkin AJ, Baumal CR, Fujimoto JG, Duker JS, Waheed NK. Visualizing the Choriocapillaris Under Drusen: Comparing 1050-nm Swept-Source Versus 840-nm Spectral-Domain Optical Coherence Tomography Angiography. Invest Ophthalmol Vis Sci. 2016 Jul 1;57(9):OCT585-90. doi: 10.1167/iovs.15-18915. PubMed PMID: 27547891; PubMed Central PMCID: PMC4995042.

Denniston AK, Sen HN. VISUALising a new framework for the treatment of uveitis. Lancet. 2016 Sep 17;388(10050):1134-6. doi: 10.1016/S0140-6736(16)31327-7. PubMed PMID: 27542304.

Full listing

View all publications in research portal

Expertise

Artificial intelligence in health; regulation of artificial intelligence; artificial intelligence in the NHS and challenges to its implementation; responsible innovation of emerging technologies