A Disease-Specific Foundation Model Using Over 100K Fundus Images: Release and Validation for Abnormality and Multi-Disease Classification on Downstream Tasks

Autor: Jang, Boa, Ahn, Youngbin, Choe, Eun Kyung, Yoon, Chang Ki, Choi, Hyuk Jin, Kim, Young-Gon

Artificial intelligence applied to retinal images offers significant potential for recognizing signs and symptoms of retinal conditions and expediting the diagnosis of eye diseases and systemic disorders. However, developing generalized artificial in

Externí odkaz: http://arxiv.org/abs/2408.08790

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A highly linear receiver front-end employing modified derivative superposition method with tuned inductors for 5.25 GHz

Autor: Ahn, Youngbin, Park, Chiwan, Lee, Jaehoon, Jeong, Jichai

Publikováno v: In Microelectronics Journal December 2010 41(12):882-888

Identification of Preeclamptic Placenta in Whole Slide Images Using Artificial Intelligence Placenta Analysis.

Autor: Jung YM; Department of Obstetrics and Gynecology, Seoul National University College of Medicine, Seoul, Korea., Park S; Department of Medical Device Development, Seoul National University College of Medicine, Seoul, Korea.; Department of Transdisciplinary Medicine, Seoul National University Hospital, Seoul, Korea., Ahn Y; Department of Transdisciplinary Medicine, Seoul National University Hospital, Seoul, Korea.; Interdisciplinary Program of Medical Informatics, Seoul National University College of Medicine, Seoul, Korea., Kim H; Department of Pathology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea., Kim EN; Department of Pathology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea., Park HE; Department of Pathology, Seoul Metropolitan Government-Seoul National University Boramae Medical Center, Seoul, Korea., Kim SM; Department of Obstetrics and Gynecology, Seoul National University College of Medicine, Seoul, Korea.; Department of Obstetrics and Gynecology, Seoul Metropolitan Government-Seoul National University Boramae Medical Center, Seoul, Korea., Kim BJ; Department of Obstetrics and Gynecology, Seoul Metropolitan Government-Seoul National University Boramae Medical Center, Seoul, Korea., Lee J; Department of Obstetrics and Gynecology, Seoul National University College of Medicine, Seoul, Korea., Park CW; Department of Obstetrics and Gynecology, Seoul National University College of Medicine, Seoul, Korea., Park JS; Department of Obstetrics and Gynecology, Seoul National University College of Medicine, Seoul, Korea., Jun JK; Department of Obstetrics and Gynecology, Seoul National University College of Medicine, Seoul, Korea., Kim YG; Department of Transdisciplinary Medicine, Seoul National University Hospital, Seoul, Korea.; Department of Medicine, Seoul National University College of Medicine, Seoul, Korea.; Innovative Medical Technology Research Institute, Seoul National University Hospital, Seoul, Korea. younggon2.kim@gmail.com., Lee SM; Department of Obstetrics and Gynecology, Seoul National University College of Medicine, Seoul, Korea.; Innovative Medical Technology Research Institute, Seoul National University Hospital, Seoul, Korea.; Department of Obstetrics and Gynecology, Seoul National University Hospital, Seoul, Korea.; Medical Big Data Research Center & Institute of Reproductive Medicine and Population, Medical Research Center, Seoul National University, Seoul, Korea. smleemd@hanmail.net.

Publikováno v: Journal of Korean medical science [J Korean Med Sci] 2024 Oct 14; Vol. 39 (39), pp. e271. Date of Electronic Publication: 2024 Oct 14.