Eyecare-cloud: an innovative electronic medical record cloud platform for pediatric research and clinical care

Knevel R, Liao KP. From real-world electronic health record data to real-world results using artificial intelligence. Ann Rheum Dis. 2023;82(3):306–11.

Article  PubMed  Google Scholar 

Uslu A, Stausberg J. Value of the electronic medical record for hospital care: update from the literature. J Med Internet Res. 2021;23(12):e26323.

Article  PubMed  PubMed Central  Google Scholar 

Das AV, Donthineni PR, Sai PG, Basu S. Allergic eye disease in children and adolescents seeking eye care in India: electronic medical records driven big data analytics report II. Ocul Surf. 2019;17(4):683–9.

Article  PubMed  Google Scholar 

Donthineni PR, Kammari P, Shanbhag SS, Singh V, Das AV, Basu S. Incidence, demographics, types and risk factors of dry eye disease in India: electronic medical records driven big data analytics report I. Ocul Surf. 2019;17(2):250–6.

Article  PubMed  Google Scholar 

Jim HSL, Hoogland AI, Brownstein NC, Barata A, Dicker AP, Knoop H, et al. Innovations in research and clinical care using patient-generated health data. CA Cancer J Clin. 2020;70(3):182–99.

Article  PubMed  PubMed Central  Google Scholar 

Miriovsky BJ, Shulman LN, Abernethy AP. Importance of health information technology, electronic health records, and continuously aggregating data to comparative effectiveness research and learning health care. J Clin Oncol. 2012;30(34):4243–8.

Article  PubMed  Google Scholar 

Bao Y, Ming WK, Mou ZW, Kong QH, Li A, Yuan TF, et al. Current application of digital diagnosing systems for retinopathy of prematurity. Comput Methods Programs Biomed. 2021;200:105871.

Article  PubMed  Google Scholar 

Golubnitschaja O, Costigliola V. 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.

Article  PubMed  PubMed Central  Google Scholar 

Arnold RW, Jacob J, Matrix Z. A cloud-based electronic medical record for scheduling, tracking, and documenting examinations and treatment of retinopathy of prematurity. J Pediatr Ophthalmol Strabismus. 2012;49(6):342–6.

Article  PubMed  Google Scholar 

Holmgren AJ, Thombley R, Sinsky CA, Adler-Milstein J. Changes in physician electronic health record use with the expansion of telemedicine. JAMA Intern Med. 2023;183(12):1357–65.

Article  PubMed  Google Scholar 

Zhou Y, Varzaneh MG. Efficient and scalable patients clustering based on medical big data in cloud platform. J Cloud Comput (Heidelb). 2022;11(1):49.

Article  PubMed  Google Scholar 

Doel T, Shakir DI, Pratt R, Aertsen M, Moggridge J, Bellon E, et al. GIFT-Cloud: a data sharing and collaboration platform for medical imaging research. Comput Methods Programs Biomed. 2017;139:181–90.

Article  PubMed  PubMed Central  Google Scholar 

DesRoches CM, Campbell EG, Rao SR, Donelan K, Ferris TG, Jha A, et al. Electronic health records in ambulatory care–a national survey of physicians. N Engl J Med. 2008;359(1):50–60.

Article  CAS  PubMed  Google Scholar 

Zhang Y, Zhang G. A domain-specific terminology for retinopathy of prematurity and its applications in clinical settings. J Healthc Eng. 2018;2018:9237319.

Article  PubMed  PubMed Central  Google Scholar 

Ghazi L, Yamamoto Y, Fuery M, O’Connor K, Sen S, Samsky M, et al. Electronic health record alerts for management of heart failure with reduced ejection fraction in hospitalized patients: the PROMPT-AHF trial. Eur Heart J. 2023;44(40):4233–42.

Article  CAS  PubMed  Google Scholar 

McKee JL, Kaufman MC, Gonzalez AK, Fitzgerald MP, Massey SL, Fung F, et al. Leveraging electronic medical record-embedded standardised electroencephalogram reporting to develop neonatal seizure prediction models: a retrospective cohort study. Lancet Digit Health. 2023;5(4):e217–26.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Overhage JM, McCallie D Jr. Physician time spent using the electronic health record during outpatient encounters: a descriptive study. Ann Intern Med. 2020;172(3):169–74.

Article  PubMed  Google Scholar 

Wilson FP, Martin M, Yamamoto Y, Partridge C, Moreira E, Arora T, et al. Electronic health record alerts for acute kidney injury: multicenter, randomized clinical trial. BMJ. 2021;372:m4786.

Article  PubMed  PubMed Central  Google Scholar 

Martin W, Sheynkman G, Lightstone FC, Nussinov R, Cheng F. Interpretable artificial intelligence and exascale molecular dynamics simulations to reveal kinetics: applications to Alzheimer’s disease. Curr Opin Struct Biol. 2022;72:103–13.

Article  CAS  PubMed  Google Scholar 

Podraza W. A new approach to neonatal medical management that could transform the prevention of retinopathy of prematurity: theoretical considerations. Med Hypotheses. 2020;137:109541.

Article  CAS  PubMed  Google Scholar 

Haug CJ, Drazen JM. Artificial intelligence and machine learning in clinical medicine, 2023. N Engl J Med. 2023;388(13):1201–8.

Article  CAS  PubMed  Google Scholar 

Lee P, Bubeck S, Petro J. Benefits, limits, and risks of GPT-4 as an AI chatbot for medicine. N Engl J Med. 2023;388(13):1233–9.

Article  PubMed  Google Scholar 

Liu Y, Du Y, Wang X, Zhao X, Zhang S, Yu Z, et al. An artificial intelligence system for screening and recommending the treatment modalities for retinopathy of prematurity. Asia Pac J Ophthalmol (Phila). 2023;12(5):468–76.

Article  CAS  PubMed  Google Scholar 

Zhang Y, Ye X, Wu W, Luo Y, Chen M, Du Y, et al. Morphological rule-constrained object detection of key structures in infant fundus image. IEEE/ACM Trans Comput Biol Bioinform. 2023.

Xie H, Zeng X, Lei H, Du J, Wang J, Zhang G, et al. Cross-attention multi-branch network for fundus diseases classification using SLO images. Med Image Anal. 2021;71:102031.

Article  PubMed  Google Scholar 

Xie H, Lei H, Zeng X, He Y, Chen G, Elazab A, et al. 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 

Xie H, Liu Y, Lei H, Song T, Yue G, Du Y, et al. Adversarial learning-based multi-level dense-transmission knowledge distillation for AP-ROP detection. Med Image Anal. 2023;84:102725.

Article  PubMed  Google Scholar 

Zhang Y, Zhang G. A domain-specific terminology for retinopathy of prematurity and its applications in clinical settings. J Healthc Eng. 2018;2018:1–6.

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. 2018;7:10232–41.

Article  Google Scholar 

Zhang Rugang, Zhao Xinyu, Xie Hai, Chen Guozhen, Zhang Guoming, Baiying Lei. Automatic diagnosis for aggressive posterior retinopathy of prematurity via deep attentive convolutional neural network. Expert Syst Appl. 2021;187:115843.

Article  Google Scholar 

Zhao J, Lei B, Wu Z, Zhang Y, Zhang G. A deep learning framework for identifying zone I in RetCam images. IEEE Access. 2019;99:1–1.

CAS  Google Scholar 

Liu Y, Xie H, Zhao X, Tang J, Yu Z, Wu Z, et al. Automated detection of nine infantile fundus diseases and conditions in retinal images using a deep learning system. EPMA J. 2024;15(1):39–51.

Article  PubMed  Google Scholar 

Hu Y, Fan Z, Zhao X, Correa Vsmc WuZ, Lu X, et al. Refractive status and biometric characteristics of children with familial exudative vitreoretinopathy. Invest Ophthalmol Vis Sci. 2023;64(13):27.

Article  PubMed  PubMed Central  Google Scholar 

Zhao J, Wu Z, Lam W, Yang M, Chen L, Zheng L, et al. Comparison of OCT angiography in children with a history of intravitreal injection of ranibizumab versus laser photocoagulation for retinopathy of prematurity. Br J Ophthalmol. 2020;104(11):1556–60.

PubMed  Google Scholar 

Wu Z, Zhao J, Lam W, Yang M, Chen L, Huang X, et al. Comparison of clinical outcomes of conbercept versus rani

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