Artificial intelligence and deep learning in ophthalmology von Ting, Daniel Shu Wei, Pasquale, Louis R, Peng, Lily, Campbell, John Peter, Lee, Aaron Y, Raman, Rajiv, Tan, Gavin Siew Wei, Schmetterer, Leopold, Keane, Pearse A, Wong, Tien Yin

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Clinically applicable deep learning for diagnosis and referral in retinal disease von De Fauw, Jeffrey, Ledsam, Joseph R., Romera-Paredes, Bernardino, Nikolov, Stanislav, Tomasev, Nenad, Blackwell, Sam, Askham, Harry, Glorot, Xavier, O’Donoghue, Brendan, Visentin, Daniel, van den Driessche, George, Lakshminarayanan, Balaji, Meyer, Clemens, Mackinder, Faith, Bouton, Simon, Ayoub, Kareem, Chopra, Reena, King, Dominic, Karthikesalingam, Alan, Hughes, Cían O., Raine, Rosalind, Hughes, Julian, Sim, Dawn A., Egan, Catherine, Tufail, Adnan, Montgomery, Hugh, Hassabis, Demis, Rees, Geraint, Back, Trevor, Khaw, Peng T., Suleyman, Mustafa, Cornebise, Julien, Keane, Pearse A., Ronneberger, Olaf

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State of science: Choroidal thickness and systemic health von Tan, Kara-Anne, MBBS, Gupta, Preeti, MOpt, Agarwal, Aniruddha, MD, Chhablani, Jay, MS, Cheng, Ching-Yu, PhD, Keane, Pearse A., FRCOphth, Agrawal, Rupesh, FRCS

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Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension von Liu, Xiaoxuan, Cruz Rivera, Samantha, Moher, David, Calvert, Melanie J., Denniston, Alastair K.

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A comparison of deep learning performance against health-care professionals in detecting diseases from medical imaging: a systematic review and meta-analysis von Liu, Xiaoxuan, Faes, Livia, Kale, Aditya U, Wagner, Siegfried K, Fu, Dun Jack, Bruynseels, Alice, Mahendiran, Thushika, Moraes, Gabriella, Shamdas, Mohith, Kern, Christoph, Ledsam, Joseph R, Schmid, Martin K, Balaskas, Konstantinos, Topol, Eric J, Bachmann, Lucas M, Keane, Pearse A, Denniston, Alastair K

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Deep learning in ophthalmology: The technical and clinical considerations von Ting, Daniel S.W., Peng, Lily, Varadarajan, Avinash V., Keane, Pearse A., Burlina, Philippe M., Chiang, Michael F., Schmetterer, Leopold, Pasquale, Louis R., Bressler, Neil M., Webster, Dale R., Abramoff, Michael, Wong, Tien Y.

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Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension von Cruz Rivera, Samantha, Liu, Xiaoxuan, Chan, An-Wen, Denniston, Alastair K., Calvert, Melanie J.

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Choroidal Vascularity Index (CVI)--A Novel Optical Coherence Tomography Parameter for Monitoring Patients with Panuveitis? von Agrawal, Rupesh, Salman, Mohammed, Tan, Kara-Anne, Karampelas, Michael, Sim, Dawn A, Keane, Pearse A, Pavesio, Carlos

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Predicting sex from retinal fundus photographs using automated deep learning von Korot, Edward, Pontikos, Nikolas, Liu, Xiaoxuan, Wagner, Siegfried K., Faes, Livia, Huemer, Josef, Balaskas, Konstantinos, Denniston, Alastair K., Khawaja, Anthony, Keane, Pearse A.

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Predicting conversion to wet age-related macular degeneration using deep learning von Yim, Jason, Chopra, Reena, Spitz, Terry, Winkens, Jim, Obika, Annette, Kelly, Christopher, Askham, Harry, Lukic, Marko, Huemer, Josef, Fasler, Katrin, Moraes, Gabriella, Meyer, Clemens, Wilson, Marc, Dixon, Jonathan, Hughes, Cian, Rees, Geraint, Khaw, Peng T., Karthikesalingam, Alan, King, Dominic, Hassabis, Demis, Suleyman, Mustafa, Back, Trevor, Ledsam, Joseph R., Keane, Pearse A., De Fauw, Jeffrey

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Forecasting future Humphrey Visual Fields using deep learning von Wen, Joanne C, Lee, Cecilia S, Keane, Pearse A, Xiao, Sa, Rokem, Ariel S, Chen, Philip P, Wu, Yue, Lee, Aaron Y

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Deep Learning for Predicting Refractive Error From Retinal Fundus Images von Varadarajan, Avinash V, Poplin, Ryan, Blumer, Katy, Angermueller, Christof, Ledsam, Joe, Chopra, Reena, Keane, Pearse A, Corrado, Greg S, Peng, Lily, Webster, Dale R

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Optical Coherence Tomography Angiography for Anterior Segment Vasculature Imaging von Ang, Marcus, FRCSEd, Sim, Dawn A., FRCOphth, Keane, Pearse A., FRCOphth, Sng, Chelvin C.A., FRCSEd, Egan, Catherine A., FRCOphth, Tufail, Adnan, FRCOphth, Wilkins, Mark R., FRCOphth

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Quantitative Analysis of OCT for Neovascular Age-Related Macular Degeneration Using Deep Learning von Moraes, Gabriella, Fu, Dun Jack, Wilson, Marc, Khalid, Hagar, Wagner, Siegfried K., Korot, Edward, Ferraz, Daniel, Faes, Livia, Kelly, Christopher J., Spitz, Terry, Patel, Praveen J., Balaskas, Konstantinos, Keenan, Tiarnan D.L., Keane, Pearse A., Chopra, Reena

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Predicting Visual Acuity by Using Machine Learning in Patients Treated for Neovascular Age-Related Macular Degeneration von Rohm, Markus, Tresp, Volker, Müller, Michael, Kern, Christoph, Manakov, Ilja, Weiss, Maximilian, Sim, Dawn A., Priglinger, Siegfried, Keane, Pearse A., Kortuem, Karsten

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A global review of publicly available datasets for ophthalmological imaging: barriers to access, usability, and generalisability von Khan, Saad M, Liu, Xiaoxuan, Nath, Siddharth, Korot, Edward, Faes, Livia, Wagner, Siegfried K, Keane, Pearse A, Sebire, Neil J, Burton, Matthew J, Denniston, Alastair K

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Biomarkers and Surrogate Endpoints in Uveitis: The Impact of Quantitative Imaging von Denniston, Alastair K, Keane, Pearse A, Srivastava, Sunil K

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Sensitivity and Specificity of Spectral-Domain Optical Coherence Tomography in Detecting Idiopathic Polypoidal Choroidal Vasculopathy von De Salvo, Gabriella, Vaz-Pereira, Sara, Keane, Pearse A, Tufail, Adnan, Liew, Gerald

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Optical Coherence Tomography–Based Observation of the Natural History of Drusenoid Lesion in Eyes with Dry Age-related Macular Degeneration von Ouyang, Yanling, MD, Heussen, Florian M., MD, Hariri, Amirhossein, MD, Keane, Pearse A., MD, MRCOphth, Sadda, SriniVas R., MD

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Predicting optical coherence tomography-derived diabetic macular edema grades from fundus photographs using deep learning von Varadarajan, Avinash V., Bavishi, Pinal, Ruamviboonsuk, Paisan, Chotcomwongse, Peranut, Venugopalan, Subhashini, Narayanaswamy, Arunachalam, Cuadros, Jorge, Kanai, Kuniyoshi, Bresnick, George, Tadarati, Mongkol, Silpa-archa, Sukhum, Limwattanayingyong, Jirawut, Nganthavee, Variya, Ledsam, Joseph R., Keane, Pearse A., Corrado, Greg S., Peng, Lily, Webster, Dale R.

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