Search Results - "Tyler Hyungtaek Rim"

Ethnic differences in the incidence of pterygium in a multi-ethnic Asian population: the Singapore Epidemiology of Eye Diseases Study by Fang, Xiao Ling, Chong, Crystal Chun Yuen, Thakur, Sahil, Da Soh, Zhi, Teo, Zhen Ling, Majithia, Shivani, Lim, Zhi Wei, Rim, Tyler Hyungtaek, Sabanayagam, Charumathi, Wong, Tien Yin, Cheng, Ching-Yu, Tham, Yih-Chung

“…We evaluated the 6-year incidence and risk factors of pterygium in a multi-ethnic Asian population. Participants who attended the baseline visit of the…”
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Efficacy of deep learning-based artificial intelligence models in screening and referring patients with diabetic retinopathy and glaucoma by Surya, Janani, Pandy, Neha, Hyungtaek Rim, Tyler, Lee, Geunyoung, Priya, M, Subramanian, Brughanya, Raman, Rajiv

“…Purpose: To analyze the efficacy of a deep learning (DL)-based artificial intelligence (AI)-based algorithm in detecting the presence of diabetic retinopathy…”
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Association between Macular Thickness Profiles and Visual Function in Healthy Eyes: The Singapore Epidemiology of Eye Diseases (SEED) Study by Poh, Stanley, Tham, Yih-Chung, Chee, Miao Li, Dai, Wei, Majithia, Shivani, Soh, Zhi Da, Fenwick, Eva K., Tao, Yijin, Thakur, Sahil, Rim, Tyler Hyungtaek, Sabanayagam, Charumathi, Cheng, Ching-Yu

“…This study aimed to evaluate the association between optical coherence tomography (OCT)-measured retinal layer thickness parameters with clinical and…”
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Adopting machine learning to automatically identify candidate patients for corneal refractive surgery by Yoo, Tae Keun, Ryu, Ik Hee, Lee, Geunyoung, Kim, Youngnam, Kim, Jin Kuk, Lee, In Sik, Kim, Jung Sub, Rim, Tyler Hyungtaek

“…Recently, it has become more important to screen candidates that undergo corneal refractive surgery to prevent complications. Until now, there is still no…”
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Retinal Vein Occlusion and the Risk of Stroke Development by Rim, Tyler Hyungtaek, MD, MBA, Kim, Dong Wook, PhD, Han, John Seungsoo, MD, Chung, Eun Jee, MD, PhD

“…Purpose To evaluate the risk of stroke development after retinal vein occlusion (RVO). Design Nationwide, population-based 9-year longitudinal study…”
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Incidence, Comorbidity, and Mortality of Primary Congenital Glaucoma in Korea from 2001 to 2015: A Nationwide Population-based Study by Seung Jae Lee, Sangah Kim, Tyler Hyungtaek Rim, Haeyong Pak, Dong Wook Kim, Jong Woon Park

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Multi-categorical deep learning neural network to classify retinal images: A pilot study employing small database by Choi, Joon Yul, Yoo, Tae Keun, Seo, Jeong Gi, Kwak, Jiyong, Um, Terry Taewoong, Rim, Tyler Hyungtaek

“…Deep learning emerges as a powerful tool for analyzing medical images. Retinal disease detection by using computer-aided diagnosis from fundus image has…”
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Trends of Pars Plana Vitrectomy Rates in South Korea: A Nationwide Cohort Study by Joo Yeon Kim, Tyler Hyungtaek Rim, Sung Soo Kim

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Artificial Intelligence Screening for Diabetic Retinopathy: the Real-World Emerging Application by Bellemo, Valentina, Lim, Gilbert, Rim, Tyler Hyungtaek, Tan, Gavin S. W., Cheung, Carol Y., Sadda, SriniVas, He, Ming-guang, Tufail, Adnan, Lee, Mong Li, Hsu, Wynne, Ting, Daniel Shu Wei

“…Purpose of Review This paper systematically reviews the recent progress in diabetic retinopathy screening. It provides an integrated overview of the current…”
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Deep learning in glaucoma with optical coherence tomography: a review by Ran, An Ran, Tham, Clement C., Chan, Poemen P., Cheng, Ching-Yu, Tham, Yih-Chung, Rim, Tyler Hyungtaek, Cheung, Carol Y.

“…Deep learning (DL), a subset of artificial intelligence (AI) based on deep neural networks, has made significant breakthroughs in medical imaging, particularly…”
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Differences among Ophthalmology Patients Referred to Tertiary Medical Centers according to Referral Hospital by Heesuk Kim, Hong Kyu Kim, Tyler Hyungtaek Rim, Ji Won Kim, Jin Hyung Kim, Sung Soo Kim

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A deep-learning system for the assessment of cardiovascular disease risk via the measurement of retinal-vessel calibre by Cheung, Carol Y., Xu, Dejiang, Cheng, Ching-Yu, Sabanayagam, Charumathi, Tham, Yih-Chung, Yu, Marco, Rim, Tyler Hyungtaek, Chai, Chew Yian, Gopinath, Bamini, Mitchell, Paul, Poulton, Richie, Moffitt, Terrie E., Caspi, Avshalom, Yam, Jason C., Tham, Clement C., Jonas, Jost B., Wang, Ya Xing, Song, Su Jeong, Burrell, Louise M., Farouque, Omar, Li, Ling Jun, Tan, Gavin, Ting, Daniel S. W., Hsu, Wynne, Lee, Mong Li, Wong, Tien Y.

“…Retinal blood vessels provide information on the risk of cardiovascular disease (CVD). Here, we report the development and validation of deep-learning models…”
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Retinal photograph-based deep learning predicts biological age, and stratifies morbidity and mortality risk by Nusinovici, Simon, Rim, Tyler Hyungtaek, Yu, Marco, Lee, Geunyoung, Tham, Yih-Chung, Cheung, Ning, Chong, Crystal Chun Yuen, Da Soh, Zhi, Thakur, Sahil, Lee, Chan Joo, Sabanayagam, Charumathi, Lee, Byoung Kwon, Park, Sungha, Kim, Sung Soo, Kim, Hyeon Chang, Wong, Tien-Yin, Cheng, Ching-Yu

“…ageing is an important risk factor for a variety of human pathologies. Biological age (BA) may better capture ageing-related physiological changes compared…”
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Updates in deep learning research in ophthalmology by Ng, Wei Yan, Zhang, Shihao, Wang, Zhaoran, Ong, Charles Jit Teng, Gunasekeran, Dinesh V, Lim, Gilbert Yong San, Zheng, Feihui, Tan, Shaun Chern Yuan, Tan, Gavin Siew Wei, Rim, Tyler Hyungtaek, Schmetterer, Leopold, Ting, Daniel Shu Wei

“…Ophthalmology has been one of the early adopters of artificial intelligence (AI) within the medical field. Deep learning (DL), in particular, has garnered…”
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Incidence and prevalence of uveitis in South Korea: a nationwide cohort study by Rim, Tyler Hyungtaek, Kim, Sung Soo, Ham, Don-Il, Yu, Seung-Young, Chung, Eun Jee, Lee, Sung Chul

“…To evaluate the incidence and prevalence of uveitis and associated risk factors in South Korea. For this retrospective national cohort study, approximately 1…”
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Prediction of systemic biomarkers from retinal photographs: development and validation of deep-learning algorithms by Rim, Tyler Hyungtaek, Lee, Geunyoung, Kim, Youngnam, Tham, Yih-Chung, Lee, Chan Joo, Baik, Su Jung, Kim, Young Ah, Yu, Marco, Deshmukh, Mihir, Lee, Byoung Kwon, Park, Sungha, Kim, Hyeon Chang, Sabayanagam, Charumathi, Ting, Daniel S W, Wang, Ya Xing, Jonas, Jost B, Kim, Sung Soo, Wong, Tien Yin, Cheng, Ching-Yu

“…The application of deep learning to retinal photographs has yielded promising results in predicting age, sex, blood pressure, and haematological parameters…”
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Validation of a deep-learning-based retinal biomarker (Reti-CVD) in the prediction of cardiovascular disease: data from UK Biobank by Tseng, Rachel Marjorie Wei Wen, Rim, Tyler Hyungtaek, Shantsila, Eduard, Yi, Joseph K, Park, Sungha, Kim, Sung Soo, Lee, Chan Joo, Thakur, Sahil, Nusinovici, Simon, Peng, Qingsheng, Kim, Hyeonmin, Lee, Geunyoung, Yu, Marco, Tham, Yih-Chung, Bakhai, Ameet, Leeson, Paul, Lip, Gregory Y H, Wong, Tien Yin, Cheng, Ching-Yu

“…Currently in the United Kingdom, cardiovascular disease (CVD) risk assessment is based on the QRISK3 score, in which 10% 10-year CVD risk indicates clinical…”
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A nationwide cohort study of cigarette smoking and risk of neovascular age-related macular degeneration in East Asian men by Rim, Tyler Hyungtaek, Cheng, Ching-Yu, Kim, Dong Wook, Kim, Sung Soo, Wong, Tien Y

“…Few longitudinal studies have evaluated the relationship between cigarette smoking and risk of neovascular age-related macular degeneration (AMD) among Asian…”
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The incidence and prevalence of pterygium in South Korea: A 10-year population-based Korean cohort study by Rim, Tyler Hyungtaek, Kang, Min Jae, Choi, Moonjung, Seo, Kyoung Yul, Kim, Sung Soo

“…Although numerous population-based studies have reported the prevalences and risk factors for pterygium, information regarding the incidence of pterygium is…”
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Refractive Errors in Koreans: The Korea National Health and Nutrition Examination Survey 2008-2012 by Tyler Hyungtaek Rim, Seung-Hyun Kim, Key Hwan Lim, Moonjung Choi, Hye Young Kim, Seung-Hee Baek

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