Retinal photograph-based deep learning system for detection of hyperthyroidism: a multicenter, diagnostic study

被引:0
作者
Li Dong
Lie Ju
Shiqi Hui
Lihua Luo
Xue Jiang
Zihan Nie
Ruiheng Zhang
Wenda Zhou
Heyan Li
Jost B. Jonas
Xin Wang
Xin Zhao
Chao He
Yuzhong Chen
Zhaohui Wang
Jianxiong Gao
Zongyuan Ge
Wenbin Wei
Dongmei Li
机构
[1] Capital Medical University,Beijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology & Visual Sciences Key Lab, Medical Artificial Intelligence Research and Verification Key Laboratory of the Min
[2] Beijing Airdoc Technology Co.,Department of Ophthalmology, Beijing Friendship Hospital
[3] Ltd,Department of Ophthalmology, Medical Faculty Mannheim
[4] Capital Medical University,Faculty of Engineering
[5] Heidelberg University,Faculty of Engineering
[6] Institute of Molecular and Clinical Ophthalmology Basel,undefined
[7] IOB,undefined
[8] Privatpraxis Prof Jonas Und Dr Panda-Jonas,undefined
[9] iKang Guobin Healthcare Group Co.,undefined
[10] Monash University,undefined
[11] ECSE,undefined
[12] Monash University,undefined
来源
Journal of Big Data | / 10卷
关键词
Artificial intelligence; Deep learning; Hyperthyroidism; Thyrotoxicosis; Retinal photographs; Retina;
D O I
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  • [1] Mullur R(2014)Thyroid hormone regulation of metabolism Physiol Rev 94 355-undefined
  • [2] Liu YY(2016)Hyperthyroidism Lancet 87 489-undefined
  • [3] Brent GA(2002)Serum TSH, T(4), and thyroid antibodies in the United States population (1988 to 1994) national health and nutrition examination survey (NHANES III) J Clin Endocrinol Metab 26 1343-undefined
  • [4] De Leo S(2016)2016 american thyroid association guidelines for diagnosis and management of hyperthyroidism and other causes of thyrotoxicosis Thyroid 99 923-undefined
  • [5] Lee SY(2014)The incidence and prevalence of thyroid dysfunction in Europe: a meta-analysis J Clin Endocrinol Metab 268 506-undefined
  • [6] Braverman LE(2018)Hyperthyroidism is underdiagnosed and undertreated in 3336 patients: an opportunity for improvement and intervention Ann Surg 521 436-undefined
  • [7] Hollowell JG(2015)Deep learning Nature 2 158-undefined
  • [8] Staehling NW(2018)Prediction of cardiovascular risk factors from retinal fundus photographs via deep learning Nature Biomed Eng 59 2861-undefined
  • [9] Flanders WD(2018)Deep learning for predicting refractive error from retinal fundus images Invest Ophthalmol Visual Sci 76 714-undefined
  • [10] Ross DS(2019)Augmented bladder tumor detection using deep learning Eur Urol 316 2402-undefined