[1]张远林 谭思远 李远杉 徐泽全 卢熙 徐旭 李俊峰 唐毅 彭建强 郑昭芬 李艳红.医疗大数据在心血管疾病的应用:潜力与挑战[J].心血管病学进展,2022,(7):605-609.[doi:10.16806/j.cnki.issn.1004-3934.2022.07.000]
 ZHANG Yuanlin,TAN Siyuan,LI Yuanshan,et al.Application of Healthcare Big Data in Cardiovascular Disease:Potential and Challenges[J].Advances in Cardiovascular Diseases,2022,(7):605-609.[doi:10.16806/j.cnki.issn.1004-3934.2022.07.000]
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医疗大数据在心血管疾病的应用:潜力与挑战()
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《心血管病学进展》[ISSN:51-1187/R/CN:1004-3934]

卷:
期数:
2022年7期
页码:
605-609
栏目:
综述
出版日期:
2022-07-25

文章信息/Info

Title:
Application of Healthcare Big Data in Cardiovascular Disease:Potential and Challenges
文章编号:
202203
作者:
张远林1 谭思远 2 李远杉1 徐泽全1 卢熙1 徐旭1 李俊峰1 唐毅 3 彭建强 3 郑昭芬 3 李艳红4
(1.湖南省人民医院信息中心 湖南师范大学附属第一医院,湖南 长沙 410005;2. 湖南师范大学附属第一医院,湖南 长沙 410005;3. 湖南省人民医院心血管内科 湖南省心力衰竭临床医学研究中心 湖南师范大学附属第一医院 ,湖南 长沙 410005;4.湖南省人民医院 湖南师范大学附属第一医院,湖南 长沙 410005)
Author(s):
ZHANG Yuanlin1TAN Siyuan2LI Yuanshan1XU Zequan1LU Xi1XU Xu1LI Junfeng1TANG Yi3 PENG Jianqiang3ZHENG Zhaofen3LI Yanhong4
(1.Information Center of Hunan Provincial Peoples Hospital,The First Affiliated Hospital of Hunan Normal University,Changsha 410005,Hunan,China; 2.The First Affiliated Hospital of Hunan Normal University,Changsha 410005,Hunan,China; 3.Department of Cardiology,Hunan Provincial Peoples Hospital,Clinical Medicine Research Center of Heart Failure of Hunan Province,The First Affiliated Hospital of Hunan Normal University,Changsha 410005,Hunan,China; 4.Hunan Provincial Peoples Hospital,The First Affiliated Hospital of Hunan Normal University,Changsha 410005,Hunan,China)
关键词:
大数据精准医疗心血管疾病
Keywords:
Big dataPrecision medicineCardiovascular disease
DOI:
10.16806/j.cnki.issn.1004-3934.2022.07.000
摘要:
越来越多的医疗机构通过电子健康档案、组学、医学影像资料和可穿戴设备等作为健康和疾病相关的电子记录,并将这些记录数据用于研究。将医学实践作为证据的基于数据和精确医疗的新时代正在到来。通过对大量数据进行整合分析,识别危险因素与疾病的相关性并进行风险预测,最终改善疾病的治疗和预后。现就医疗大数据的特性及来源、大数据分析的技术、大数据在心血管疾病研究中的优势以及面临的挑战做一综述。
Abstract:
More and more medical institutions use electronic health records,omics,medical imaging materials and wearable devices as electronic records related to health and disease,and use these recorded data for research. A new era of data-based and precision medicine based on medical practice as evidence is coming. Through integrated analysis of large amounts of data,the correlation between risk factors and diseases can be identified and the risk prediction can be made to improve the treatment and prognosis of diseases. The characteristics and sources of medical big data,the tools of big data analysis,the advantages of big data in the research of cardiovascular disease,the challenges faced by big data are described in this paper

参考文献/References:

[1].Jensen PB,Jensen LJ,Brunak S. Mining electronic health records:towards better research applications and clinical care[J]. Nat Rev Genet,2012,13(6):395-405.
[2].Hemingway H,Asselbergs FW,Danesh J,et al. Big data from electronic health records for early and late translational cardiovascular research:challenges and potential[J]. Eur Heart J ,2018,39(16):1481-1495.
[3].Alonso SG,de la Torre Díez I,Rodrigues JJPC,et al. A systematic review of techniques and sources of big data in the healthcare sector[J]. J Med Syst,2017,41(11):183.
[4].Zhong RY,Newman ST,Huang GQ,et al. Big data for supply chain management in the service and manufacturing sectors:challenges,opportunities,and future perspectives[J]. Comput Ind Eng,2016,101:572-591.
[5].Nambiar R,Bhardwaj R,Sethi A,et al. A look at challenges and opportunities of Big Data analytics in healthcare[J]. IEEE Int Conf Big Data,2013,2013:17-22.
[6].Berger ML,Doban V. Big data,advanced analytics and the future of comparative effectiveness research[J]. J Comp Effect Res,2014,3(2):167-176.
[7].Tawalbeh LA,Mehmood R,Benkhelifa E,et al. Mobile cloud computing model and big data analysis for healthcare applications[J]. IEEE Access,2017,4(99):6171-6180.
[8].Iván,García-Magario,Raquel,et al. Agent-based simulation of smart beds with Internet-of-Things for exploring big data analytics[J]. IEEE Access,2017,6(99):366-379.
[9].Nazir S,Nawaz M,Adnan A,et al. Big data features,applications,and analytics in cardiology—A systematic literature review[J]. IEEE Access ,2019,PP(99): 1-1.
[10].Rahimi K,Bennett D,Conrad N,et al. Risk prediction in patients with heart failure:a systematic review and analysis[J]. JACC Heart Fail ,2014,2(5):440-446.
[11].Jindal A,Dua A,Kumar N,et al. Providing Healthcare-as-a-Service using fuzzy rule-based big data analytics in cloud computing[J]. IEEE J Biomed Health Inform, 2018,22(5):1605-1618.
[12].Reeves RM,Christensen L,Brown JR,et al. Adaptation of an NLP system to a new healthcare environment to identify social determinants of health[J]. J Biomed Inform,2021,120:103851.
[13].Monaco C,Mathur A,Martin JF. What causes acute coronary syndromes? Applying Koch’s postulates[J]. Atherosclerosis,2005,179(1):1-15.
[14].Bates DW,Saria S,Ohno-Machado L,et al. Big data in health care:using analytics to identify and manage high-risk and high-cost patients[J]. Health Aff(Millwood),2014,33(7):1123-1131.
[15].Collins FS,Varmus H. A new initiative on precision medicine[J]. N Engl J Med,2015,372(9):793-795.
[16].Shameer K,Johnson KW,Yahi A,et al. Predictive modeling of hospital readmision rates using electronic medical record-wide machine learning:a case-study using Mount Sinai heart failure cohort[J]. Pac Symp Biocomput ,2017,22:276-287.
[17].Parkes J,Bryant J,Milne R. Implantable cardioverter defibrillators:arrhythmias. A rapid and systematic review[J]. Health Technol Assess,2000,4(26):1-69.
[18].Evangelou E,Warren HR,Mosen-Ansorena D,et al. Genetic analysis of over 1 million people identifies 535 new loci associated with blood pressure traits[J]. Nat Genet,2018,50(10):1412-1425.
[19].Kim J. Big data,health informatics,and the future of cardiovascular medicine[J]. J Am Coll Cardiol,2017,69(7):899-902.
[20].Obermeyer Z,Emanuel EJ. Predicting the future—Big data,machine learning,and clinical medicine[J]. N Engl J Med,2016,375(13):1216-1219.
[21].Sahoo AK,Mallik S,Pradhan C,et al. Intelligence-based health recommendation system using big data analytics[M]. Cambridge,MA:Academic Press,2019:227-246,
[22].Rastegar-Mojarad M,Ye Z,Kolesar JM,et al. Opportunities for drug repositioning from phenome-wide association studies[J]. Nat Biotechnol,2015,33(4):342.
[23].Casas JP,Hingorani AD. The interleukin-6 receptor as a target for prevention of coronary heart disease:a Mendelian randomisation analysis[J]. Lancet,2012,379(9822):1214-1224.
[24].Wang G,Jung K,Winnenburg R,et al. A method for systematic discovery of adverse drug events from clinical notes[J]. J Am Med Inform Assoc ,2015,22(6):1196-1204.
[25].Noor A. A data-driven medical decision framework for associating adverse drug events with drug-drug interaction mechanisms[J]. J Healthc Eng,2022,2022:9132477.
[26].Luo J,Wu M,Gopukumar D,et al. Big data application in biomedical research and health care. A l iterature review[J]. Biomed Inform Insights,2016,19(8):1-10.
[27].Galetsi P,Katsaliaki K,Kumar S. Values,challenges and future directions of big data analytics in healthcare:a systematic review[J]. Soc Sci Med ,2019,241:112533.
[28].Jensen AB,Moseley PL,Oprea TI,et al. Temporal disease trajectories condensed from population-wide registry data covering 6.2 million patients[J]. Nat Commmun,2014,5(1):4022-4032.
[29].Morley KI,Wallace J,Denaxas SC,et al. Defining disease phenotypes using national linked electronic health records:a case study of atrial fibrillation[J]. PLoS One,2014,9(11):e110900.
[30].Leopold JA,Maron BA,Loscalzo J. The application of big data to cardiovascular disease:paths to precision medicine[J]. J Clin Invest,2020,130(1):29-38.
[31].Vermeer AMC,Clur SB,Blom NA,et al. Penetrance of hypertrophic cardiomyopathy in children who are mutation positive[J]. J Pediatr,2017,188:91-95.
[32].Ghiassian SD,Menche J,Chasman DI,et al. Endophenotype network models:common core of complex diseases[J]. Sci Rep,2016,6:27414.
[33].Roque FS,Jensen PB,Schmock H,et al. Using electronic patient records to discover disease correlations and stratify patient cohorts[J]. PLoS Comput B iol,2011,7(8):e1002141.
[34].Kitchin R. Big data and human geography opportunities,challenges and risks[J]. Dialogues Hum Geogr,2013,3(3):262-267.
[35].Denaxas SC,Julie G,Emily H,et al. Data resource profile:cardiovascular disease research using linked bespoke studies and electronic health records(CALIBER)[J]. Int J Epidemiol,2012,41(6):1625-1638.
[36].Denny JC,Bastarache L,Ritchie MD,et al. Systematic comparison of phenome-wide association study of electronic medical record data and genome-wide association study data[J]. Nat Biotechnol,2013,31(12):1102-1111.
[37].Abul-Husn NS,Kenny EE. Personalized medicine and the power of electronic health records[J]. Cell,2019,177(1):58-69.
[38].Blumenthal D,Tavenner M. The “meaningful use” regulation for electronic health records[J]. N Engl J Med, 2010,363(6):501-504.
[39].Nanjo A,Evans H,Direk K,et al. Prevalence,incidence,and outcomes across cardiovascular diseases in homeless individuals using national linked electronic health records[J]. Eur Heart J,2020,41(41):4011-4020.
[40].Li B,Li J,Jiang Y,et al. Experience and reflection from China’s Xiangya medical big data project[J]. J Biomed Inform,2019,93:103149.
[41].Zhang L,Wang H,Li Q,et al. Big data and medical research in China[J]. BMJ,2018,360:j5910.
[42].Shan L,Wu Q,Liu C,et al. Perceived challenges to achieving universal health coverage:a cross-sectional survey of social health insurance managers/administrators in China[J]. BMJ Open,2017,7(5):e014425.
[43].Bikash,Kanti,Sarkar. Big data for secure healthcare system:a conceptual design[J]. Complex Intell Syst,2017,3(2):133-151.
[44].Wu J,Ota K,Dong M,et al. Big data analysis-based security situational awareness for smart grid[J]. IEEE T Big Data,2016,408-417.
[45].Pfeilschifter W,Luger S,Brunkhorst R,et al. The gap between trial data and clinical practice—An analysis of case reports on bleeding complications occurring under dabigatran and rivaroxaban anticoagulation[J]. Cerebrovasc Dis,2013,36(2):115-119.
[46].Detmer DE,Shortliffe EH. Clinical informatics:prospects for a new medical subspecialty[J]. JAMA,2014,311(20):2067-2068.
[47].Farshad,Firouzi,Bahar,et al. Keynote paper:from EDA to IoT eHealth:promises,challenges,and solutions[J]. IEEE T Comput Aid D,2018,37(12):2965-2978.

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更新日期/Last Update: 2022-08-22