Tufail, Adnan

Clinically applicable deep learning for diagnosis and referral in retinal disease

De Fauw, J., Ledsam, J. R., Romera-Paredes, B., Nikolov, S., Tomasev, N., Blackwell, S., Askham, H., Glorot, X., O’Donoghue, B., Visentin, D., et al. (2018) · Nature Medicine

Retinal Imaging and AnalysisRetinal Diseases and Treatments

Cited by 2,639

A foundation model for generalizable disease detection from retinal images

Zhou, Y., Chia, M. A., Wagner, S. K., Ayhan, M. S., Williamson, D. J., Struyven, R. R., Liu, T., Xu, M., Lozano, M. G., Woodward-Court, P., et al. (2023) · Nature

Retinal Imaging and AnalysisOphthalmology and Visual Health Research

Cited by 1,014

Defining response to anti-VEGF therapies in neovascular AMD

Amoaku, W. M., Chakravarthy, U., Gale, R., Gavin, M., Ghanchi, F., Gibson, J., Harding, S., Johnston, R. L., Kelly, S., Lotery, A., et al. (2015) · Eye

Retinal Diseases and TreatmentsOcular Diseases and Behçet’s Syndrome

Cited by 355

Automated Diabetic Retinopathy Image Assessment Software

Tufail, A., Rudisill, C., Egan, C., Kapetanakis, V. V., Salas-Vega, S., Owen, C. G., Lee, A., Louw, V., Anderson, J., Liew, G., et al. (2017) · Ophthalmology

Retinal Imaging and AnalysisRetinal Diseases and Treatments

Cited by 283

Trustworthy AI: Closing the gap between development and integration of AI systems in ophthalmic practice

González-Gonzalo, C., Thee, E. F., Klaver, C. C. W., Lee, A. Y., Schlingemann, R. O., Tufail, A., Verbraak, F., & Sánchez, C. I. (2022) · Progress in Retinal and Eye Research

Artificial Intelligence in Healthcare and EducationEthics and Social Impacts of AI

Cited by 103

The Neovascular Age-Related Macular Degeneration Database

Zarranz-Ventura, J., Liew, G., Johnston, R. L., Xing, W., Akerele, T., McKibbin, M., Downey, L., Natha, S., Chakravarthy, U., Bailey, C., et al. (2014) · Ophthalmology

Retinal Diseases and TreatmentsRetinal and Macular Surgery

Cited by 103

Evaluation of Shared Genetic Susceptibility to High and Low Myopia and Hyperopia

Tideman, J. W. L., Pärssinen, O., Haarman, A. E. G., Khawaja, A. P., Wedenoja, J., Williams, K. M., Biino, G., Ding, X., Kähönen, M., Lehtimäki, T., et al. (2021) · JAMA Ophthalmology

Ophthalmology and Visual Impairment StudiesGenetic Associations and Epidemiology

Cited by 56

Retinal Asymmetry in Multiple Sclerosis

Petzold, A., Chua, S. Y. L., Khawaja, A. P., Keane, P. A., Khaw, P. T., Reisman, C., Dhillon, B., Strouthidis, N. G., Foster, P. J., Patel, P. J., et al. (2021) · Brain

Multiple Sclerosis Research StudiesGlaucoma and retinal disorders

Cited by 56

Incidence and baseline clinical characteristics of treated neovascular age-related macular degeneration in a well-defined region of the UK

Keenan, T. D. L., Kelly, S. P., Sallam, A., Mohamed, Q., Tufail, A., & Johnston, R. L. (2013) · British Journal of Ophthalmology

Retinal Diseases and TreatmentsOcular Diseases and Behçet’s Syndrome

Cited by 29

Patient and practitioner perceptions around use of artificial intelligence within the English NHS diabetic eye screening programme

Wahlich, C., Chandrasekaran, L., Chaudhry, U. A. R., Willis, K., Chambers, R., Bolter, L., Anderson, J., Shakespeare, R., Olvera-Barrios, A., Fajtl, J., et al. (2025) · Diabetes Research and Clinical Practice

Artificial Intelligence in Healthcare and EducationRetinal Imaging and Analysis

Cited by 13