Automated detection of nine infantile fundus diseases and conditions in retinal images using a deep learning system

Chiang MF, Quinn GE, Fielder AR, Ostmo SR, Paul Chan RV, Berrocal A, et al. International Classification of Retinopathy of Prematurity, Third Edition. Ophthalmology. 2021;128(10):e51–68. https://doi.org/10.1016/j.ophtha.2021.05.031.

Article  PubMed  Google Scholar 

Shields JA, Shields CL, Honavar SG, Demirci H. Clinical variations and complications of Coats disease in 150 cases: the 2000 Sanford Gifford Memorial Lecture. Am J Ophthalmol. 2001;131(5):561–71. https://doi.org/10.1016/s0002-9394(00)00883-7.

Article  CAS  PubMed  Google Scholar 

Spitznas M, Joussen F, Wessing A, Meyer-Schwickerath G. Coat’s disease. An epidemiologic and Fluorescein angiographic study. Albrecht Von Graefes Arch Klin Exp Ophthalmol. 1975;195(4):241–50. https://doi.org/10.1007/BF00414937.

Article  CAS  PubMed  Google Scholar 

Rao R, Honavar SG. Retinoblastoma. Indian J Pediatr. 2017;84(12):937–44. https://doi.org/10.1007/s12098-017-2395-0.

Article  PubMed  Google Scholar 

Pagon RA. Retinitis pigmentosa. Surv Ophthalmol. 1988;33(3):137–77. https://doi.org/10.1016/0039-6257(88)90085-9.

Article  MathSciNet  CAS  PubMed  Google Scholar 

Giles K, Raoul C, Yannick B, Peter W. Uveal coloboma: about 3 cases at the University Teaching Hospital, Yaounde, Cameroon. Pan Afr Med J. 2016;24:201. https://doi.org/10.11604/pamj.2016.24.201.9770.

Article  PubMed  PubMed Central  Google Scholar 

Nishina S, Suzuki Y, Yokoi T, Kobayashi Y, Noda E, Azuma N. Clinical features of congenital retinal folds. Am J Ophthalmol. 2012;153(1):81-7 e1. https://doi.org/10.1016/j.ajo.2011.06.002.

Article  PubMed  Google Scholar 

Liche F, Majji AB. Familial exudative vitreoretinopathy. Ophthalmology. 2012;119(5):1093. https://doi.org/10.1016/j.ophtha.2012.02.025.

Article  PubMed  Google Scholar 

Fielder A, Blencowe H, O’Connor A, Gilbert C. Impact of retinopathy of prematurity on ocular structures and visual functions. Arch Dis Child Fetal Neonatal Ed. 2015;100(2):F179–84. https://doi.org/10.1136/archdischild-2014-306207.

Article  PubMed  Google Scholar 

Golubnitschaja O, Costigliola V, Epma. General report & recommendations in predictive, preventive and personalised medicine 2012: white paper of the European Association for Predictive, Preventive and Personalised Medicine. EPMA J. 2012;3(1):14. https://doi.org/10.1186/1878-5085-3-14.

Article  PubMed  PubMed Central  Google Scholar 

Good WV. Retinopathy of Prematurity Incidence in Children. Ophthalmology. 2020;127(4S):S82–3. https://doi.org/10.1016/j.ophtha.2019.11.026.

Article  PubMed  Google Scholar 

Dimaras H, Corson TW, Cobrinik D, White A, Zhao J, Munier FL, et al. Retinoblastoma. Nat Rev Dis Primers. 2015;1:15021. https://doi.org/10.1038/nrdp.2015.21.

Article  PubMed  PubMed Central  Google Scholar 

Global Retinoblastoma Study G, Fabian ID, Abdallah E, Abdullahi SU, Abdulqader RA, Adamou Boubacar S, et al. Global Retinoblastoma Presentation and Analysis by National Income Level. JAMA Oncol. 2020;6(5):685–95. https://doi.org/10.1001/jamaoncol.2019.6716.

Article  Google Scholar 

Chen HY, Lehmann OJ, Swaroop A. Genetics and therapy for pediatric eye diseases. EBioMedicine. 2021;67:103360. https://doi.org/10.1016/j.ebiom.2021.103360.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Coleman K, Coleman J, Franco-Penya H, Hamroush F, Murtagh P, Fitzpatrick P, et al. A New Smartphone-Based Optic Nerve Head Biometric for Verification and Change Detection. Transl Vis Sci Technol. 2021;10(8):1. https://doi.org/10.1167/tvst.10.8.1.

Article  PubMed  PubMed Central  Google Scholar 

Golubnitschaja O, Potuznik P, Polivka J Jr, Pesta M, Kaverina O, Pieper CC, et al. Ischemic stroke of unclear aetiology: a case-by-case analysis and call for a multi-professional predictive, preventive and personalised approach. EPMA J. 2022;13(4):535–45. https://doi.org/10.1007/s13167-022-00307-z.

Article  PubMed  PubMed Central  Google Scholar 

Topol EJ. High-performance medicine: the convergence of human and artificial intelligence. Nat Med. 2019;25(1):44–56. https://doi.org/10.1038/s41591-018-0300-7.

Article  CAS  PubMed  Google Scholar 

Baek SU, Lee WJ, Park KH, Choi HJ. Health screening program revealed risk factors associated with development and progression of papillomacular bundle defect. EPMA J. 2021;12(1):41–55. https://doi.org/10.1007/s13167-021-00235-4.

Article  PubMed  PubMed Central  Google Scholar 

Li S, Li M, Wu J, Li Y, Han J, Cao W, et al. Development and validation of a routine blood parameters-based model for screening the occurrence of retinal detachment in high myopia in the context of PPPM. EPMA J. 2023;14(2):219–33. https://doi.org/10.1007/s13167-023-00319-3.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Golub TR, Slonim DK, Tamayo P, Huard C, Gaasenbeek M, Mesirov JP, et al. Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. Science. 1999;286(5439):531–7. https://doi.org/10.1126/science.286.5439.531.

Article  CAS  PubMed  Google Scholar 

Wang Y, Tetko IV, Hall MA, Frank E, Facius A, Mayer KF, et al. Gene selection from microarray data for cancer classification–a machine learning approach. Comput Biol Chem. 2005;29(1):37–46. https://doi.org/10.1016/j.compbiolchem.2004.11.001.

Article  CAS  PubMed  Google Scholar 

Yu KH, Levine DA, Zhang H, Chan DW, Zhang Z, Snyder M. Predicting Ovarian Cancer Patients’ Clinical Response to Platinum-Based Chemotherapy by Their Tumor Proteomic Signatures. J Proteome Res. 2016;15(8):2455–65. https://doi.org/10.1021/acs.jproteome.5b01129.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Yu KH, Fitzpatrick MR, Pappas L, Chan W, Kung J, Snyder M. Omics AnalySIs System for PRecision Oncology (OASISPRO): a web-based omics analysis tool for clinical phenotype prediction. Bioinformatics. 2018;34(2):319–20. https://doi.org/10.1093/bioinformatics/btx572.

Article  CAS  PubMed  Google Scholar 

Check Hayden E. The automated lab. Nature. 2014;516(7529):131–2. https://doi.org/10.1038/516131a.

Article  ADS  CAS  PubMed  Google Scholar 

Chew EY. Age-related Macular Degeneration: Nutrition, Genes and Deep Learning-The LXXVI Edward Jackson Memorial Lecture. Am J Ophthalmol. 2020;217:335–47. https://doi.org/10.1016/j.ajo.2020.05.042.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Shon K, Sung KR, Shin JW. Can Artificial Intelligence Predict Glaucomatous Visual Field Progression? A Spatial-Ordinal Convolutional Neural Network Model. Am J Ophthalmol. 2022;233:124–34. https://doi.org/10.1016/j.ajo.2021.06.025.

Article  PubMed  Google Scholar 

Ee CL, Samsudin A. Comparison of Smartphone-Based and Automated Refraction with Subjective Refraction for Screening of Refractive Errors. Ophthalmic Epidemiol. 2022;29(5):588–94. https://doi.org/10.1080/09286586.2021.1986550.

Article  PubMed  Google Scholar 

Dai L, Wu L, Li H, Cai C, Wu Q, Kong H, et al. A deep learning system for detecting diabetic retinopathy across the disease spectrum. Nat Commun. 2021;12(1):3242. https://doi.org/10.1038/s41467-021-23458-5.

Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

Panwar N, Huang P, Lee J, Keane PA, Chuan TS, Richhariya A, et al. Fundus Photography in the 21st Century–A Review of Recent Technological Advances and Their Implications for Worldwide Healthcare. Telemed J E Health. 2016;22(3):198–208. https://doi.org/10.1089/tmj.2015.0068.

Article  PubMed  PubMed Central  Google Scholar 

Zhao J, Lei B, Wu Z, Zhang Y, Li Y, Wang L, et al. A Deep Learning Framework for Identifying Zone I in RetCam Images. IEEE Access. 2019;7:103530–7. https://doi.org/10.1109/access.2019.2930120.

Article  Google Scholar 

Zhang Y, Wang L, Wu Z, Zeng J, Chen Y, Tian R, et al. Development of an Automated Screening System for Retinopathy of Prematurity Using a Deep Neural Network for Wide-Angle Retinal Images. IEEE Access. 2019;7:10232–41. https://doi.org/10.1109/access.2018.2881042.

Article  Google Scholar 

Rugang Zhang JZ. Hai Xie, Tianfu Wang, Automatic diagnosis for aggressive posterior retinopathy of prematurity via deep attentive convolutional neural network. Expert Syst Appl. 2022;187:115843.

Article  Google Scholar 

Maji D, Sekh AA. Automatic grading of retinal blood vessel in deep retinal image diagnosis. J Med Syst. 2020;44(180). https://doi.org/10.1007/s10916-020-01635-1.

Xie HLH, Zeng X, He Y, Chen G. AMD-GAN: attention encoder and multi-branch structure based generative adversarial networks for fundus disease detection from scanning laser ophthalmoscopy images. Neural Netw. 2020;132:477–90.

Article  PubMed  Google Scholar 

Dong L, He W, Zhang R, Ge Z, Wang YX, Zhou J, et al. Artificial Intelligence for Screening of Multiple Retinal and Optic Nerve Diseases. JAMA Netw Open. 2022;5(5):e229960. https://doi.org/10.1001/jamanetworkopen.2022.9960.

Article  PubMed 

留言 (0)

沒有登入
gif