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Galetsi P, Katsaliaki K. Big data analytics in health: an overview and bibliometric study of research activity. Health Info Libr J. 2020;37:5–25.GaletsiPKatsaliakiK.Big data analytics in health: an overview and bibliometric study of research activity. Health Info Libr J. 2020;37:5–25.Search in Google Scholar
Rains SA. Big data, computational social science, and health communication: a review and agenda for advancing theory. Health Commun. 2020;35: 26–34.RainsSA.Big data, computational social science, and health communication: a review and agenda for advancing theory. Health Commun. 2020;35: 26–34.Search in Google Scholar
Fanelli S, Pratici L, Salvatore FP, Donelli CC, Zangrandi A. Big data analysis for decision-making processes: challenges and opportunities for the management of health-care organizations. Manag Res Rev. 2023;46:369–389.FanelliSPraticiLSalvatoreFPDonelliCCZangrandiA.Big data analysis for decision-making processes: challenges and opportunities for the management of health-care organizations. Manag Res Rev. 2023;46:369–389.Search in Google Scholar
Finkelstein J, Zhang F, Levitin SA, Cappelli D. Using big data to promote precision oral health in the context of a learning healthcare system. J Public Health Dent. 2020;80:S43–S58.FinkelsteinJZhangFLevitinSACappelliD.Using big data to promote precision oral health in the context of a learning healthcare system. J Public Health Dent. 2020;80:S43–S58.Search in Google Scholar
Monsen KA, Peters J, Schlesner S, Vanderboom CE, Holland DE. The gap in big data: getting to wellbeing, strengths, and a whole-person perspective. Glob Adv Health Med. 2015;4:31–39.MonsenKAPetersJSchlesnerSVanderboomCEHollandDE.The gap in big data: getting to wellbeing, strengths, and a whole-person perspective. Glob Adv Health Med. 2015;4:31–39.Search in Google Scholar
Bani Hani SH, Ahmad MM. Large-scale data in health care: a concept analysis. Georgian Med News. 2022;325:33–36.Bani HaniSHAhmadMM.Large-scale data in health care: a concept analysis. Georgian Med News. 2022;325:33–36.Search in Google Scholar
Wong HT, Chiang VCL, Choi KS, Loke AY. The need for a definition of Big Data for nursing science: a case study of disaster preparedness. Int J Environ Res Public Health. 2016;13:1015.WongHTChiangVCLChoiKSLokeAY.The need for a definition of Big Data for nursing science: a case study of disaster preparedness. Int J Environ Res Public Health. 2016;13:1015.Search in Google Scholar
Sensmeier J. Understanding the impact of big data on nursing knowledge. Nurs2019 Crit Care. 2016;11:11–13.SensmeierJ.Understanding the impact of big data on nursing knowledge. Nurs2019 Crit Care. 2016;11:11–13.Search in Google Scholar
Zhu R, Han S, Su Y, Zhang C, Yu Q, Duan Z. The application of big data and the development of nursing science: a discussion paper. Int J Nurs Sci. 2019;6:229–234.ZhuRHanSSuYZhangCYuQDuanZ.The application of big data and the development of nursing science: a discussion paper. Int J Nurs Sci. 2019;6:229–234.Search in Google Scholar
Westra BL, Clancy TR, Sensmeier J, Warren JJ, Weaver C, Delaney CW. Nursing knowledge: big data science—implications for nurse leaders. Nurs Adm Q. 2015;39:304–310.WestraBLClancyTRSensmeierJWarrenJJWeaverCDelaneyCW.Nursing knowledge: big data science—implications for nurse leaders. Nurs Adm Q. 2015;39:304–310.Search in Google Scholar
Bani Hani SH, Ahmad MM. Machine-learning algorithms for ischemic heart disease prediction: a systematic review. Curr Cardiol Rev. 2023;19:87–99.Bani HaniSHAhmadMM.Machine-learning algorithms for ischemic heart disease prediction: a systematic review. Curr Cardiol Rev. 2023;19:87–99.Search in Google Scholar
Brennan PF, Bakken S. Nursing needs big data and big data needs nursing. J Nurs Scholarsh. 2015;47:477–484.BrennanPFBakkenS.Nursing needs big data and big data needs nursing. J Nurs Scholarsh. 2015;47:477–484.Search in Google Scholar
Moher D, Liberati A, Tetzlaff J, Altman DG; PRISMA Group. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 2009;6:e1000097.MoherDLiberatiATetzlaffJAltmanDGPRISMA Group. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 2009;6:e1000097.Search in Google Scholar
Stifter J, Yao Y, Lodhi MK, et al. Nurse continuity and hospital-acquired pressure ulcers: A comparative analysis using an electronic health record “big data” set. Nurs Res. 2015;64:361–371.StifferJYaoYLodhiMK, Nurse continuity and hospital-acquired pressure ulcers: A comparative analysis using an electronic health record “big data” set. Nurs Res. 2015;64:361–371.Search in Google Scholar
Remus S. The big data revolution: opportunities for chief nurse executives. Nurs Leadersh. 2016;28:18–28.RemusS.The big data revolution: opportunities for chief nurse executives. Nurs Leadersh. 2016;28:18–28.Search in Google Scholar
Founds S. Systems biology for nursing in the era of big data and precision health. Nurs Outlook. 2018;66:283–292.FoundsS.Systems biology for nursing in the era of big data and precision health. Nurs Outlook. 2018;66:283–292.Search in Google Scholar
Gleason KT, Himmelfarb CRD. Big data: Contributions, limitations, and implications for cardiovascular nurses. J Cardiovasc Nurs. 2017;32:4–6.GleasonKTHimmelfarbCRD.Big data: Contributions, limitations, and implications for cardiovascular nurses. J Cardiovasc Nurs. 2017;32:4–6.Search in Google Scholar
Procter PM, Wilson ML. Nursing, professional curiosity and big data CoCreating eHealth. In MIE (pp. 186–190).ProcterPMWilsonML.Nursing, professional curiosity and big data CoCreating eHealth. In MIE (pp. 186–190).Search in Google Scholar
Monsen KA, Kelechi TJ, McRae ME, Mathiason MA, Martin KS. Nursing theory, terminology, and big data: data-driven discovery of novel patterns in archival randomized clinical trial data. Nurs Res. 2018;67:122–132.MonsenKAKelechiTJMcRaeMEMathiasonMAMartinKS.Nursing theory, terminology, and big data: data-driven discovery of novel patterns in archival randomized clinical trial data. Nurs Res. 2018;67:122–132.Search in Google Scholar
Hewner S, Sullivan SS, Yu G. Reducing emergency room visits and in-hospitalizations by implementing best practice for transitional care using innovative technology and big data. Worldviews Evid Based Nurs. 2018;15:170–177.HewnerSSullivanSSYuG.Reducing emergency room visits and in-hospitalizations by implementing best practice for transitional care using innovative technology and big data. Worldviews Evid Based Nurs. 2018;15:170–177.Search in Google Scholar
Gleason KT, Davidson PM, Tanner EK, et al. Defining the critical role of nurses in diagnostic error prevention: a conceptual framework and a call to action. Diagnosis. 2017;4:201–210.GleasonKTDavidsonPMTannerEK, Defining the critical role of nurses in diagnostic error prevention: a conceptual framework and a call to action. Diagnosis. 2017;4:201–210.Search in Google Scholar
Clancy TR. Artificial intelligence and nursing: the future is now. J Nurs Adm. 2020;50:125–127.ClancyTR.Artificial intelligence and nursing: the future is now. J Nurs Adm. 2020;50:125–127.Search in Google Scholar