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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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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