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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New meaning for NLP: the trials and tribulations of natural language processing with GPT-3 in ophthalmology von Nath, Siddharth, Marie, Abdullah, Ellershaw, Simon, Korot, Edward, Keane, Pearse A

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Vision-Language Models for Feature Detection of Macular Diseases on Optical Coherence Tomography von Antaki, Fares, Chopra, Reena, Keane, Pearse A

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Allograft theory Transmission of devil facial-tumour disease von Pearse, A.-M, Swift, K

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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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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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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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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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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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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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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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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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Optical coherence tomography in the 2020s—outside the eye clinic von Chopra, Reena, Wagner, Siegfried K., Keane, Pearse A.

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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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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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The eye, the kidney, and cardiovascular disease: old concepts, better tools, and new horizons von Farrah, Tariq E., Dhillon, Baljean, Keane, Pearse A., Webb, David J., Dhaun, Neeraj

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AI-facilitated health care requires education of clinicians von Keane, Pearse A, Topol, Eric J

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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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