Zobrazeno 1 - 10
of 59
pro vyhledávání: '"Chotcomwongse, P."'
Publikováno v:
Ophthalmology and Therapy, Vol 13, Iss 10, Pp 2543-2558 (2024)
Abstract A large language model (LLM) is an artificial intelligence (AI) model that uses natural language processing (NLP) to understand, interpret, and generate human-like language responses from unstructured text input. Its real-time response capab
Externí odkaz:
https://doaj.org/article/787f2833ad8044bdb80fa6247d095468
Autor:
Chantra S, Chotcomwongse P, Jittreprasert S, Senarak W, Amornpetchsathaporn A, Kemchoknatee P, Ruamviboonsuk P
Publikováno v:
Clinical Ophthalmology, Vol Volume 17, Pp 2845-2860 (2023)
Somporn Chantra,1,2 Peranut Chotcomwongse,1 Supachase Jittreprasert,1 Wirapha Senarak,1,* Anyarak Amornpetchsathaporn,1,* Parinee Kemchoknatee,1,2 Paisan Ruamviboonsuk1,2 1Department of Ophthalmology, Rajavithi Hospital, Bangkok, Thailand; 2C
Externí odkaz:
https://doaj.org/article/5f4b5f5c4a9b49d29ba108c823df406f
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Autor:
Raumviboonsuk, Paisan, Krause, Jonathan, Chotcomwongse, Peranut, Sayres, Rory, Raman, Rajiv, Widner, Kasumi, Campana, Bilson J L, Phene, Sonia, Hemarat, Kornwipa, Tadarati, Mongkol, Silpa-Acha, Sukhum, Limwattanayingyong, Jirawut, Rao, Chetan, Kuruvilla, Oscar, Jung, Jesse, Tan, Jeffrey, Orprayoon, Surapong, Kangwanwongpaisan, Chawawat, Sukulmalpaiboon, Ramase, Luengchaichawang, Chainarong, Fuangkaew, Jitumporn, Kongsap, Pipat, Chualinpha, Lamyong, Saree, Sarawuth, Kawinpanitan, Srirat, Mitvongsa, Korntip, Lawanasakol, Siriporn, Thepchatri, Chaiyasit, Wongpichedchai, Lalita, Corrado, Greg S, Peng, Lily, Webster, Dale R
Deep learning algorithms have been used to detect diabetic retinopathy (DR) with specialist-level accuracy. This study aims to validate one such algorithm on a large-scale clinical population, and compare the algorithm performance with that of human
Externí odkaz:
http://arxiv.org/abs/1810.08290
Autor:
Varadarajan, Avinash, Bavishi, Pinal, Raumviboonsuk, Paisan, Chotcomwongse, Peranut, Venugopalan, Subhashini, Narayanaswamy, Arunachalam, Cuadros, Jorge, Kanai, Kuniyoshi, Bresnick, George, Tadarati, Mongkol, Silpa-archa, Sukhum, Limwattanayingyong, Jirawut, Nganthavee, Variya, Ledsam, Joe, Keane, Pearse A, Corrado, Greg S, Peng, Lily, Webster, Dale R
Publikováno v:
Nature Communications (2020)
Diabetic eye disease is one of the fastest growing causes of preventable blindness. With the advent of anti-VEGF (vascular endothelial growth factor) therapies, it has become increasingly important to detect center-involved diabetic macular edema (ci
Externí odkaz:
http://arxiv.org/abs/1810.10342
Autor:
Sukhum Silpa-archa, Akkaranisorn Dejkong, Kwanchanoke Kumsiang, Peranut Chotcomwongse, Janine M Preble, C. Stephen Foster
Publikováno v:
International Journal of Ophthalmology, Vol 13, Iss 12, Pp 1968-1975 (2020)
AIM: To demonstrate prognostic factors for poor visual outcome in patients with post-traumatic endophthalmitis (PTE) following open globe injury. METHODS: A retrospective study was conducted on 66 patients (66 eyes) with PTE following open globe inj
Externí odkaz:
https://doaj.org/article/014627cf1db74a0a9152f54451f428e3
Autor:
Avinash V. Varadarajan, Pinal Bavishi, Paisan Ruamviboonsuk, Peranut Chotcomwongse, Subhashini Venugopalan, Arunachalam Narayanaswamy, Jorge Cuadros, Kuniyoshi Kanai, George Bresnick, Mongkol Tadarati, Sukhum Silpa-archa, Jirawut Limwattanayingyong, Variya Nganthavee, Joseph R. Ledsam, Pearse A. Keane, Greg S. Corrado, Lily Peng, Dale R. Webster
Publikováno v:
Nature Communications, Vol 11, Iss 1, Pp 1-8 (2020)
Diabetic eye disease is a cause of preventable blindness and accurate and timely referral of patients with diabetic macular edema is important to start treatment. Here the authors present a deep learning model that can predict the presence of diabeti
Externí odkaz:
https://doaj.org/article/00d3202651b84a36837950c21fab3fb0
Publikováno v:
Life, Vol 12, Iss 10, p 1610 (2022)
Background: The aim of this study was to assess the performance of regional graders and artificial intelligence algorithms across retinal cameras with different specifications in classifying an image as gradable and ungradable. Methods: Study subject
Externí odkaz:
https://doaj.org/article/f740e8cccf084e1f9bd01f3b840d6218
Akademický článek
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