[1]《人工智能在神经眼科疾病诊断中的应用指南(0)》专家组,中国医药教育协会眼科影像与智能医疗分会,国际转化医学会眼科专业委员会,等.人工智能在神经眼科疾病诊断中的应用指南(2023)[J].眼科新进展,2023,43(12):925-933.[doi:10.13389/j.cnki.rao.2023.0185]
 Expert Workgroup of Guidelines for Application of Artificial Intelligence in the diagnosis of neuro-ophthalmic diseases (0),Ophthalmic Imaging and Intelligent Medicine Branch of Chinese Medicine Education Association,Ophthalmology Committee of International Association of Translational Medicine,et al.Guidelines for the application of artificial intelligence in the diagnosis of neuro-ophthalmic diseases[J].Recent Advances in Ophthalmology,2023,43(12):925-933.[doi:10.13389/j.cnki.rao.2023.0185]
点击复制

人工智能在神经眼科疾病诊断中的应用指南(2023)/HTML
分享到:

《眼科新进展》[ISSN:1003-5141/CN:41-1105/R]

卷:
43卷
期数:
2023年12期
页码:
925-933
栏目:
述评
出版日期:
2023-12-05

文章信息/Info

Title:
Guidelines for the application of artificial intelligence in the diagnosis of neuro-ophthalmic diseases
作者:
《人工智能在神经眼科疾病诊断中的应用指南(2023)》专家组中国医药教育协会眼科影像与智能医疗分会国际转化医学会眼科专业委员会中国眼科影像研究专家组
Author(s):
Expert Workgroup of Guidelines for Application of Artificial Intelligence in the diagnosis of neuro-ophthalmic diseases (2023);Ophthalmic Imaging and Intelligent Medicine Branch of Chinese Medicine Education Association;Ophthalmology Committee of International Association of Translational Medicine;Chinese Ophthalmic Imaging Study Group
关键词:
人工智能神经眼科视神经盘病变眼球运动障碍
Keywords:
artificial intelligence neuro-ophthalmology optic disc disorder eye movement disorder
分类号:
R774
DOI:
10.13389/j.cnki.rao.2023.0185
文献标志码:
A
摘要:
人工智能技术的快速发展推动了医疗保健系统的智能化进程。神经眼科是眼科领域中新兴的分支学科,其常见疾病包括视神经盘病变和眼球运动障碍等。由于机器学习和深度学习等技术的不断提高,人工智能在神经眼科疾病诊断和治疗中的应用日益广泛。本文就人工智能在神经眼科疾病诊断中的应用形成指南,为人工智能在该领域中的进一步研究和应用提供参考。
Abstract:
The rapid development of artificial intelligence technology has promoted the intelligentization of healthcare systems. Neuro-ophthalmology is an emerging branch of ophthalmology, which includes research in common diseases such as optic disc disorders and eye movement disorders. Due to the continuous improvement of machine learning and deep learning technologies, artificial intelligence is increasingly applied in the diagnosis and treatment of neuro-ophthalmic diseases. This paper aims to form a guideline on the application of artificial intelligence technology in the diagnosis of neuro-ophthalmic diseases, laying the foundation for further research and application of artificial intelligence in this field.

参考文献/References:

[1] TING D S J,FOO V H,YANG L W Y,SIA J T,ANG M,LIN H,et al.Artificial intelligence for anterior segment diseases:emerging applications in ophthalmology[J].Br J Ophthalmol,2021,105(2):158-168.
[2] TING D S W,PENG L,VARADARAJAN A V,KEANE P A,BURLINA P M,CHIANG M F,et al.Deep learning in ophthalmology:the technical and clinical considerations[J].Prog Retin Eye Res,2019,72:100759.
[3] 杨卫华,邵毅,许言午,《眼科人工智能临床研究评价指南》专家组,中国医药教育协会眼科影像与智能医疗分会,中国医药教育协会智能医学专业委员会.眼科人工智能临床研究评价指南(2023)[J].国际眼科杂志,2023,23(7):1064-1071.
YANG W H,SHAO Y,XU Y W,Expert Workgroup of Guidelines on Clinical Research Evaluation of Artificial Intelligence in Ophthalmology (2023),Ophthalmic Imaging and Intelligent Medicine Branch of Chinese Medicine Education Association,Intelligent Medicine Special Committee of Chinese Medicine Education Association.Guidelines on clinical research evaluation of artificial intelligence in ophthalmology (2023) [J].Int Eye Sci,2023,23(7):1064-1071.
[4] LEONG Y Y,VASSENEIX C,FINKELSTEIN M T,MILEA D,NAJJAR R P.Artificial intelligence meets neuro-ophthalmology[J].Asia Pac J Ophthalmol,2022,11(2):111-125.
[5] BRUCE B B,BIOUSSE V,NEWMAN N J.Nonmydriatic ocular fundus photography in neurologic emergencies[J].JAMA Neurol,2015,72(4):455.
[6] SACHDEVA V,VASSENEIX C,HAGE R,BIDOT S,CLOUGH L C,WRIGHT D W,et al.Optic nerve head edema among patients presenting to the emergency department[J].Neurology,2018,90(5):e373-e379.
[7] BIOUSSE V,BRUCE B B,NEWMAN N J.Ophthalmoscopy in the 21st century[J].Neurology,2018,90(4):167-175.
[8] AKBAR S,AKRAM M U,SHARIF M,TARIQ A,YASIN U U.Decision support system for detection of papilledema through fundus retinal images[J].J Med Syst,2017,41(4):66.
[9] TRICK G L,BHATT S S,DAHL D,SKARF B.Optic disc topography in pseudopapilledema:a comparison to pseudotumor cerebri[J].J Neuro Ophthalmol,2001,21(4):240-244.
[10] AHN J M,KIM S,AHN K S,CHO S H,KIM U S.Accuracy of machine learning for differentiation between optic neuropathies and pseudopapilledema[J].BMC Ophthalmol,2019,19:178.
[11] MILEA D,NAJJAR R P,ZHUBO Z,TING D,VASSENEIX C,XU X,et al.Artificial intelligence to detect papilledema from ocular fundus photographs[J].N Engl J Med,2020,382(18):1687-1695.
[12] BIOUSSE V,NEWMAN N J,NAJJAR R P,VASSENEIX C,XU X,TING D S,et al.Optic disc classification by deep learning versus expert neuro-ophthalmologists[J].Ann Neurol,2020,88(4):785-795.
[13] SABA T,AKBAR S,KOLIVAND H,ALI BAHAJ S.Automatic detection of papilledema through fundus retinal images using deep learning[J].Microsc Res Tech,2021,84(12):3066-3077.
[14] LIU T Y A,WEI J,ZHU H,SUBRAMANIAN P S,MYUNG D,YI P H,et al.Detection of optic disc abnormalities in color fundus photographs using deep learning[J].J Neuroophthalmol,2021,41(3):368-374.
[15] VASSENEIX C,NAJJAR R P,XU X,TANG Z,LOO J L,SINGHAL S,et al.Accuracy of a deep learning system for classification of papilledema severity on ocular fundus photographs[J].Neurology,2021,97(4):e369-e377.
[16] OSAGUONA V B.Differential diagnoses of the pale/white/atrophic disc[J].Community Eye Health,2016,29(96):71-74.
[17] YANG H K,OH J E,HAN S B,KIM K G,HWANG J M.Automatic computer-aided analysis of optic disc pallor in fundus photographs[J].Acta Ophthalmol,2019,97(4):e519-e525.
[18] CAO Z,SUN C,WANG W,ZHENG X,WU J,GAO H.Multi-modality fusion learning for the automatic diagnosis of optic neuropathy[J].Pattern Recognit Lett,2021,142:58-64.
[19] JONAS J B,AUNG T,BOURNE R R,BRON A M,RITCH R,PANDA-JONAS S.Glaucoma[J].Lancet,2017,390(10108):2183-2193.
[20] LI Z,HE Y,KEEL S,MENG W,CHANG R T,HE M.Efficacy of a deep learning system for detecting glaucomatous optic neuropathy based on color fundus photographs[J].Ophthalmology,2018,125(8):1199-1206.
[21] YANG H K,KIM Y J,SUNG J Y,KIM D H,KIM K G,HWANG J M.Efficacy for differentiating nonglaucomatous versus glaucomatous optic neuropathy using deep learning systems[J].Am J Ophthalmol,2020,216:140-146.
[22] LI F,YAN L,WANG Y,SHI J,CHEN H,ZHANG X,et al.Deep learning-based automated detection of glaucomatous optic neuropathy on color fundus photographs[J].Graefes Arch Exp Ophthalmol,2020,258(4):851-867.
[23] HENGST T C,HENGST T C,GILBERT S.Fatal flaws in the design of pediatric ophthalmology and strabismus studies[M].Berlin:Springer International Publishing,2013:59.
[24] VIIKKI K,ISOTALO E,JUHOLA M,PYYKK I.Using decision tree induction to model oculomotor data[J].Scand Audiol,2001,30(1):103-105.
[25] D’ADDIO G,RICCIARDI C,IMPROTA G,BIFULCO P,CESARELLI M.Feasibility of machine learning in predicting features related to congenital nystagmus[C]//HENRIQUES J,NEVES N,DE CARVALHO P.Mediterranean conference on medical and biological engineering and computing.Berlin:Springer International Publishing,2020:907-913.
[26] 黎彪,丁雅珺,邵毅.人工智能在小儿眼科领域的应用研究进展[J].国际眼科杂志,2020,20(8):1363-1366.
LI B,DING Y J,SHAO Y.Research progress on application of artificial intelligence in pediatric ophthalmology[J].Int Eye Sci,2020,20(8):1363-1366.
[27] DE ALMEIDA J D S,SILVA A C,TEIXEIRA J A M,PAIVA A C,GATTASS M.Computer-aided methodology for syndromic strabismus diagnosis[J].J Digit Imaging,2015,28(4):462-473.
[28] VAN EENWYK J,AGAH A,GIANGIACOMO J,CIBIS G.Artificial intelligence techniques for automatic screening of amblyogenic factors[J].Trans Am Ophthalmol Soc,2008,106:64-74.
[29] DE FIGUEIREDO L A,DIAS J V P,POLATI M,CARRICONDO P C,DEBERT I.Strabismus and artificial intelligence app:optimizing diagnostic and accuracy[J].Trans Vis Sci Tech,2021,10(7):22.
[30] ZHENG C,YAO Q,LU J,XIE X,LIN S,WANG Z,et al.Detection of referable horizontal strabismus in children’s primary gaze photographs using deep learning[J].Transl Vis Sci Technol,2021,10(1):33.
[31] LU J W,FAN Z,ZHENG C,FENG J G,HUANG L T,LI W J,et al.Automated strabismus detection for telemedicine applications[J].arXiv,2018:1809.02940v3.
[32] JUNG S M,UMIRZAKOVA S,WHANGBO T K.Strabismus classification using face features[C]//2019 International Symposium on Multimedia and Communication Technology (ISMAC).New York:IEEE,2020:1-4.
[33] CHEN Z,FU H,LO W L,CHI Z.Strabismus recognition using eye-tracking data and convolutional neural networks[J].J Healthc Eng,2018,2018:7692198.
[34] YANG H K,SEO J M,HWANG J M,KIM K G.Automated analysis of binocular alignment using an infrared camera and selective wavelength filter[J].Invest Ophthalmol Vis Sci,2013,54(4):2733-2737.
[35] VALENTE T L A,DE ALMEIDA J D S,SILVA A C,TEIXEIRA J A M,GATTASS M.Automatic diagnosis of strabismus in digital videos through cover test[J].Comput Meth Programs Biomed,2017,140:295-305.
[36] GRAMATIKOV B I.Detecting central fixation by means of artificial neural networks in a pediatric vision screener using retinal birefringence scanning[J].Biomed Eng Online,2017,16(1):52.
[37] FISHER A C,CHANDNA A,CUNNINGHAM I P.The differential diagnosis of vertical strabismus from prism cover test data using an artificially intelligent expert system[J].Med Biol Eng Comput,2007,45(7):689-693.
[38] CHANDNA A,FISHER A C,CUNNINGHAM I,STONE D,MITCHELL M.Pattern recognition of vertical strabismus using an artificial neural network (StrabNet)[J].Strabismus,2009,17(4):131-138.
[39] THURTELL M J,LEIGH R J.Treatment of nystagmus[J].Curr Treat Options Neurol,2012,14(1):60-72.
[40] ABADI R V.Mechanisms underlying nystagmus[J].J R Soc Med,2002,95(5):231-234.
[41] WAGLE N,MORKOS J,LIU J,REITH H,GREENSTEIN J,GONG K,et al.aEYE:a deep learning system for video nystagmus detection[J].Front Neurol,2022,13:963968.
[42] LI H,YANG Z.Vertical nystagmus recognition based on deep learning[J].Sensors,2023,23(3):1592.
[43] KONG S,HUANG Z,DENG W,ZHAN Y,LV J,CUI Y.Nystagmus patterns classification framework based on deep learning and optical flow[J].Comput Biol Med,2023,153:106473.
[44] NAIR A G,PATIL-CHHABLANI P,VENKATRAMANI D V,GANDHI R A.Ocular myasthenia gravis:a review[J].Indian J Ophthalmol,2014,62(10):985-991.
[45] SMITH S V,LEE A G.Update on ocular myasthenia gravis[J].Neurol Clin,2017,35(1):115-123.
[46] LIU G,WEI Y,XIE Y,LI J,QIAO L,YANG J J.A computer-aided system for ocular myasthenia gravis diagnosis[J].Tsinghua Sci Technol,2021,26(5):749-758.
[47] SHIH K C,LAM K S L,TONG L.A systematic review on the impact of diabetes mellitus on the ocular surface[J].Nutr Diabetes,2017,7(3):e251.
[48] GWATHMEY K G,PEARSON K T.Diagnosis and management of sensory polyneuropathy[J].BMJ,2019,365:l1108.
[49] WEN X,LI Z,XIAO J H,LIU X,ZHANG Y,LAN Y.Association of myopia with microvascular alterations in patients with type 2 diabetes:an optical coherence tomography angiography study[J].Front Med (Lausanne),2021,8:715074.
[50] KIRTHI V,PERUMBALATH A,BROWN E,NEVITT S,PETROPOULOS I N,BURGESS J,et al.Prevalence of peripheral neuropathy in pre-diabetes:a systematic review[J].BMJ Open Diabetes Res Care,2021,9(1):e002040.
[51] WILLIAMS B M,BORRONI D,LIU R,ZHAO Y,ZHANG J,LIM J,et al.An artificial intelligence-based deep learning algorithm for the diagnosis of diabetic neuropathy using corneal confocal microscopy:a development and validation study[J].Diabetologia,2020,63(2):419-430.
[52] TEH K,ARMITAGE P,TESFAYE S,SELVARAJAH D.Deep learning classification of treatment response in diabetic painful neuropathy:a combined machine learning and magnetic resonance neuroimaging methodological study[J].Neuroinformatics,2023,21(1):35-43.
[53] MOU L,QI H,LIU Y,ZHENG Y,MATTHEW P,SU P,et al.DeepGrading:deep learning grading of corneal nerve tortuosity[J].IEEE Trans Med Imaging,2022,41(8):2079-2091.
[54] LEE I H,MILLER N R,ZAN E,TAVARES F,BLITZ A M,SUNG H,et al.Visual defects in patients with pituitary adenomas:the myth of bitemporal Hemianopsia[J].Am J Roentgenol,2015,205(5):W512-W518.
[55] OGRA S,NICHOLS A D,STYLLI S,KAYE A H,SAVINO P J,DANESH-MEYER H V.Visual acuity and pattern of visual field loss at presentation in pituitary adenoma[J].J Clin Neurosci,2014,21(5):735-740.
[56] DRUMMOND S R,WEIR C.Chiasmal compression misdiagnosed as normal-tension glaucoma:can we avoid the pitfalls?[J].Int Ophthalmol,2010,30(2):215-219.
[57] GREENFIELD D S,SIATKOWSKI R M,GLASER J S,SCHATZ N J,PARRISH R K 2nd.The cupped disc.Who needs neuroimaging?[J].Ophthalmology,1998,105(10):1866-1874.
[58] THOMAS P B M,CHAN T,NIXON T,MUTHUSAMY B,WHITE A.Feasibility of simple machine learning approaches to support detection of non-glaucomatous visual fields in future automated glaucoma clinics[J].Eye,2019,33(7):1133-1139.
[59] KARA S,GVEN A.Neural network-based diagnosing for optic nerve disease from visual-evoked potential[J].J Med Syst,2007,31(5):391-396.
[60] GVEN A,POLAT K,KARA S,GNE?瘙塁 S.The effect of generalized discriminate analysis (GDA) to the classification of optic nerve disease from VEP signals[J].Comput Biol Med,2008,38(1):62-68.
[61] MAO Y,HE Y,LIU L,CHEN X.Disease classification based on eye movement features with decision tree and random forest[J].Front Neurosci,2020,14:798.
[62] TUTAN A M,IONESCU B,SANTARNECCHI E.Artificial intelligence in neurodegenerative diseases:a review of available tools with a focus on machine learning techniques[J].Artif Intell Med,2021,117:102081.
[63] NAM U,LEE K,KO H,LEE J Y,LEE E C.Analyzing facial and eye movements to screen for Alzheimer’s disease[J].Sensors,2020,20(18):5349.
[64] CHEUNG C Y,RAN A R,WANG S,CHAN V T T,SHAM K,HILAL S,et al.A deep learning model for detection of Alzheimer’s disease based on retinal photographs:a retrospective,multicentre case-control study[J].Lancet Digit Health,2022,4(11):e806-e815.
[65] QIAO N,SONG M,YE Z,HE W,MA Z,WANG Y,et al.Deep learning for automatically visual evoked potential classification during surgical decompression of sellar region tumors[J].Transl Vis Sci Technol,2019,8(6):21.
[66] 魏世辉,宋宏鲁.我国神经眼科的十年回顾与展望[J].中华眼底病杂志,2020,36(4):253-256.
WEI S H,SONG H L.The review and prospect of the decade of neuro-ophthalmology in China[J].Chin J Ocul Fundus Dis,2020,36(4):253-256.
[67] 孙铁,张雨晴,邵毅.人工智能及其在眼科疾病诊疗中的应用[J].眼科新进展,2020,40(8):793-796,800.
SUN T,ZHANG Y Q,SHAO Y.The application of artificial intelligence on ophthalmic diseases[J].Rec Adv Ophthalmol,2020,40(8):793-796,800.
[68] 《人工智能在干眼临床诊断中的应用专家共识(2023)》专家组,中国医药教育协会眼科影像与智能医疗分会,中国人口文化促进会角膜病与眼表疾病分会.人工智能在干眼临床诊断中的应用专家共识(2023)[J].眼科新进展,2023,43(4):253-259.
Expert Consensus on Clinical Application of Artificial Intelligence in Dry Eyes (2023) Expert Group,Ophthalmic Imaging and Intelligent Medicine Branch of China Medical Education Association,Corneal and Ocular Surface Diseases Branch of Chinese Population and Society Promotion Association.Expert consensus on clinical application of artificial intelligence in dry eyes(2023) [J].Rec Adv Ophthalmol,2023,43(4):253-259.
[69] 《眼科人工智能临床应用伦理专家共识》专家组,中国医药教育协会数字影像与智能医疗分会,中国医药教育协会智能医学专业委员会.眼科人工智能临床应用伦理专家共识(2023)[J].中华实验眼科杂志,2023,41(1):1-7.
Expert Workgroup of Expert consensus for ethics of clinical application of artificial intelligence in ophthalmology (2023),Digital Imaging and Intelligent Medicine Branch of China Medical Education Association,Intelligent Medicine Special Committee of China Medical Education Association.Expert consensus for ethics of clinical application of artificial intelligence in ophthalmology(2023)[J].Chin J Exp Ophthalmol,2023,41(1):1-7.
[70] CHAN E J J,NAJJAR R P,TANG Z,MILEA D.Deep learning for retinal image quality assessment of optic nerve head disorders[J].Asia Pac J Ophthalmol,2021,10(3):282-288.

相似文献/References:

[1]赵金凤,吴桢泉,郑磊,等.人工智能在眼科疾病诊疗的应用现状[J].眼科新进展,2019,39(5):495.[doi:10.13389/j.cnki.rao.2019.0114]
 ZHAO Jin-Feng,WU Zhen-Quan,ZHENG Lei,et al.Application of artificial intelligence in the diagnosis and treatment of ocular diseases[J].Recent Advances in Ophthalmology,2019,39(12):495.[doi:10.13389/j.cnki.rao.2019.0114]
[2]余燕,侯银芬,吴昌凡,等.人工智能深度学习技术在常见眼病辅助诊断的应用现状和进展[J].眼科新进展,2020,40(4):396.[doi:10.13389/j.cnki.rao.2020.0092]
 YU Yan,HOU Yinfen,WU Changfan,et al.Application and progress of artificial intelligence deep learning technology in diagnosis of common eye diseases[J].Recent Advances in Ophthalmology,2020,40(12):396.[doi:10.13389/j.cnki.rao.2020.0092]
[3]孙铁,张雨晴,邵毅.人工智能及其在眼科疾病诊疗中的应用[J].眼科新进展,2020,40(8):793.[doi:10.13389/j.cnki.rao.2020.0181]
 SUN Tie,ZHANG Yuqing,SHAO Yi.The application of artificial intelligence on ophthalmic diseases[J].Recent Advances in Ophthalmology,2020,40(12):793.[doi:10.13389/j.cnki.rao.2020.0181]
[4]郑武,阮坤炜,吴天添,等.人工智能糖尿病视网膜病变筛查系统与眼科医师诊断结果的一致性分析[J].眼科新进展,2020,40(12):1170.[doi:10.13389/j.cnki.rao.2020.0260]
 ZHENG Wu,RUAN Kunwei,WU Tiantian,et al.Consistency of artificial intelligence screening system with ophthalmologist for diagnosing of diabetic retinopathy[J].Recent Advances in Ophthalmology,2020,40(12):1170.[doi:10.13389/j.cnki.rao.2020.0260]
[5]《人工智能在干眼临床诊断中的应用专家共识(0)》专家组,中国医药教育协会眼科影像与智能医疗分会,中国人口文化促进会角膜病与眼表疾病分会.人工智能在干眼临床诊断中的应用专家共识(2023)[J].眼科新进展,2023,43(4):253.[doi:10.13389/j.cnki.rao.2023.0052]
 Expert Consensus on Clinical Application of Artificial Intelligence in Dry Eyes (0) Expert Group,Ophthalmic Imaging and Intelligent Medicine Branch of China Medical Education Association,Corneal and Ocular Surface Diseases Branch of Chinese Population and Society Promotion Association.Expert consensus on clinical application of artificial intelligence in dry eyes (2023)[J].Recent Advances in Ophthalmology,2023,43(12):253.[doi:10.13389/j.cnki.rao.2023.0052]
[6]杨丽丹,李青蒨,陈倩茵,等.人工智能在青光眼诊断中的研究进展[J].眼科新进展,2023,43(6):500.[doi:10.13389/j.cnki.rao.2023.0102]
 YANG Lidan,LI Qingqian,CHEN Qianyin,et al.Research progress of artificial intelligence in the diagnosis of glaucoma[J].Recent Advances in Ophthalmology,2023,43(12):500.[doi:10.13389/j.cnki.rao.2023.0102]
[7]《人工智能辅助诊断早产儿视网膜病变应用指南(0)》专家组,中国医药教育协会眼科影像与智能医疗分会,国际转化医学会眼科专委会,等.人工智能辅助诊断早产儿视网膜病变应用指南(2023)[J].眼科新进展,2023,43(9):673.[doi:10.13389/j.cnki.rao.2023.0136]
 Expert Workgroup of Guidelines for the Application of Artificial Intelligence in Retinopathy of Premature Infants0,Ophthalmic Imaging and Intelligent Medicine Branch of Chinese Medicine Education Association,Ophthalmology Committee of International Association of Translational Medicine,et al.Guidelines for the application of artificial intelligence in the auxiliary diagnosis of retinopathy of prematurity (2023)[J].Recent Advances in Ophthalmology,2023,43(12):673.[doi:10.13389/j.cnki.rao.2023.0136]
[8]《人工智能在甲状腺相关性眼病中的应用指南(0)》专家组,中国医药教育协会眼科影像与智能医疗分会,中国医师协会眼科分会眼肿瘤专委会,等.人工智能在甲状腺相关性眼病中的应用指南(2023)[J].眼科新进展,2023,43(11):841.[doi:10.13389/j.cnki.rao.2023.0169]
 Expert Workgroup of Guidelines for the Application of Artificial Intelligence in Thyroid Associated Ophthalmopathy(0),Ophthalmic Imaging and Intelligent Medicine Branch of Chinese Medicine Education Association,Ocular Oncology Committee of the Ophthalmology Branch of the Chinese Medical Doctor Association,et al.Guidelines for the application of artificial intelligence in thyroid-associated ophthalmopathy (2023)[J].Recent Advances in Ophthalmology,2023,43(12):841.[doi:10.13389/j.cnki.rao.2023.0169]
[9]任章军,余进海,桑泽曦,等.人工智能深度学习在眼眶病及眼肿瘤疾病诊疗中的应用研究现状[J].眼科新进展,2024,44(2):163.[doi:10.13389/j.cnki.rao.2024.0032]
 REN Zhangjun,YU Jinhai,SANG Zexi,et al.Research advancement of the application of artificial intelligence deep learning in the diagnosis and treatment of orbital diseases and ocular tumors[J].Recent Advances in Ophthalmology,2024,44(12):163.[doi:10.13389/j.cnki.rao.2024.0032]
[10]陈铭海,白芳,陶海.多模态数据融合技术及其在眼科领域的应用研究进展[J].眼科新进展,2024,44(3):248.[doi:10.13389/j.cnki.rao.2024.0049]
 CHEN Minghai,BAI Fang,TAO Hai.Multimodal data fusion and research progress of its application in ophthalmology[J].Recent Advances in Ophthalmology,2024,44(12):248.[doi:10.13389/j.cnki.rao.2024.0049]

备注/Memo

备注/Memo:
国家自然科学基金(编号:82160195);江西省双千计划科技创新高端领军人才项目(编号:jxsq2023201036);江西省重大(重点)研发专项计划(编号:20223BBH80014)
注:本指南的国际实践指南注册号为 PREPARE-2023CN483(http://www.guidelines-redistry.cn/)。
更新日期/Last Update: 2023-12-05