Artificial intelligence for diabetic retinopathy screening, prediction and management von Gunasekeran, Dinesh V., Ting, Daniel S.W., Tan, Gavin S.W., Wong, Tien Y.

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Digital technology, tele-medicine and artificial intelligence in ophthalmology: A global perspective von Li, Ji-Peng Olivia, Liu, Hanruo, Ting, Darren S.J., Jeon, Sohee, Chan, R.V. Paul, Kim, Judy E., Sim, Dawn A., Thomas, Peter B.M., Lin, Haotian, Chen, Youxin, Sakomoto, Taiji, Loewenstein, Anat, Lam, Dennis S.C., Pasquale, Louis R., Wong, Tien Y., Lam, Linda A., Ting, Daniel S.W.

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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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Visual Neglect Following Stroke: Current Concepts and Future Focus von Ting, Darren S.J., MBChB, Pollock, Alex, PhD, Dutton, Gordon N., MD, FRCOphth, Doubal, Fergus N., MRCP, Ting, Daniel S.W., MBBS, Thompson, Michelle, BSc (Hons), Dhillon, Baljean, FRCPS, FRCS, FRCOphth

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Preparedness among Ophthalmologists: During and Beyond the COVID-19 Pandemic von Olivia Li, Ji-Peng, Shantha, Jessica, Wong, Tien Y., Wong, Edmund Y., Mehta, Jod, Lin, Haotian, Lin, Xiaofeng, Strouthidis, Nicholas G., Park, Ki Ho, Fung, Adrian T., McLeod, Stephen D., Busin, Massimo, Parke, David W., Holland, Gary N., Chodosh, James, Yeh, Steven, Ting, Daniel S.W.

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An Ophthalmologist's Guide to Deciphering Studies in Artificial Intelligence von Ting, Daniel S.W., Lee, Aaron Y., Wong, Tien Y.

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Interpretation of artificial intelligence studies for the ophthalmologist von Tan, Tien-En, Xu, Xinxing, Wang, Zhaoran, Liu, Yong, Ting, Daniel S.W.

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The next generation of healthcare ecosystem in the metaverse von Li, Yong, Gunasekeran, Dinesh Visva, RaviChandran, Narrendar, Tan, Ting Fang, Ong, Jasmine Chiat Ling, Thirunavukarasu, Arun James, Polascik, Bryce W., Habash, Ranya, Khaderi, Khizer, Ting, Daniel S.W.

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Automated and Computer-Assisted Detection, Classification, and Diagnosis of Diabetic Retinopathy von Abràmoff, Michael D, Leng, Theodore, Ting, Daniel S W, Rhee, Kyu, Horton, Mark B, Brady, Christopher J, Chiang, Michael F

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Emerging Ethical Considerations for the Use of Artificial Intelligence in Ophthalmology von Evans, Nicholas G., Wenner, Danielle M., Cohen, I. Glenn, Purves, Duncan, Chiang, Michael F., Ting, Daniel S.W., Lee, Aaron Y.

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Cross-modality Labeling Enables Noninvasive Capillary Quantification as a Sensitive Biomarker for Assessing Cardiovascular Risk von Shi, Danli, Zhou, Yukun, He, Shuang, Wagner, Siegfried K., Huang, Yu, Keane, Pearse A., Ting, Daniel S.W., Zhang, Lei, Zheng, Yingfeng, He, Mingguang

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Feasibility study of sustained-release travoprost punctum plug for intraocular pressure reduction in an Asian population von Perera, Shamira A, Ting, Daniel Sw, Nongpiur, Monisha E, Chew, Paul T, Aquino, Maria Cecilia D, Sng, Chelvin Ca, Ho, Sue-Wei, Aung, Tin

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Real-World Treatment Outcomes of Age-Related Macular Degeneration and Polypoidal Choroidal Vasculopathy in Asians von Fenner, Beau J., Ting, Daniel S.W., Tan, Anna C.S., Teo, Kelvin, Chan, Choi Mun, Mathur, Ranjana, Yeo, Ian Y.S., Wong, Tien Y., Wong, Edmund Y.M., Cheung, Chui Ming Gemmy

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Novel Retinal Imaging in Assessment of Cardiovascular Risk Factors and Systemic Vascular Diseases von Ting, Daniel S.W., Peng, Lily, Varadarajan, Avinash V., Liu, Tin Yan Alvin

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Retinal Video Recording von Ting, Daniel S.W., MBBS(Hons), Tay-Kearney, Mei Ling, FRANZCO, Constable, Ian, FRANZCO, Lim, Liam, FRANZCO, Preen, David B., PhD, Kanagasingam, Yogesan, PhD

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AI for medical imaging goes deep von Ting, Daniel S. W., Liu, Yong, Burlina, Philippe, Xu, Xinxing, Bressler, Neil M., Wong, Tien Y.

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Artificial intelligence for diabetic retinopathy screening: a review von Grzybowski, Andrzej, Brona, Piotr, Lim, Gilbert, Ruamviboonsuk, Paisan, Tan, Gavin S. W., Abramoff, Michael, Ting, Daniel S. W.

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The promise of artificial intelligence: a review of the opportunities and challenges of artificial intelligence in healthcare von Aung, Yuri Y M, Wong, David C S, Ting, Daniel S W

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Diagnostic accuracy of deep learning in medical imaging: a systematic review and meta-analysis von Aggarwal, Ravi, Sounderajah, Viknesh, Martin, Guy, Ting, Daniel S. W., Karthikesalingam, Alan, King, Dominic, Ashrafian, Hutan, Darzi, Ara

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Developing specific reporting guidelines for diagnostic accuracy studies assessing AI interventions: The STARD-AI Steering Group von Sounderajah, Viknesh, Ashrafian, Hutan, Aggarwal, Ravi, De Fauw, Jeffrey, Denniston, Alastair K., Greaves, Felix, Karthikesalingam, Alan, King, Dominic, Liu, Xiaoxuan, Markar, Sheraz R., McInnes, Matthew D. F., Panch, Trishan, Pearson-Stuttard, Jonathan, Ting, Daniel S. W., Golub, Robert M., Moher, David, Bossuyt, Patrick M., Darzi, Ara

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