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醫療大數據及其應用

Big Health Data and Its Applications

摘要


大數據(bigdata)意指數量龐大、更新快速、內容複雜,人工不易處理的資料。在醫療領域,數位資料從電子病歷、生物特徵、醫學影像、社群媒體等各種來源不斷湧現。從複雜、大量,而且充滿雜訊的資料裡分析出有價值的資訊,會遇到容量、時效性、多樣性、準確性等方面的挑戰,而雲端運算與機器學習等資訊科技有助於克服這些挑戰。目前海量醫療數據已經應用於就診建議、診斷支援、風險預測、資源管理、公共衛生、疾病預防等方面,讓醫療資源的運用更有效率,促進人類個體與群體的健康。

並列摘要


Big data means a large amount of data that are too complex and too fleet to be managed by human. In the area of healthcare, millions of new data appear from various sources such as electronic health records, biometric data, medical images, and social media data. To analyze the structured/unstructured information in big health data, four challenges are indicated: volume, velocity, variety, and veracity (4Vs). The information technologies like cloud computing and machine learning help overcome these challenges. Big health data are currently applied in outpatient recommendation, clinical decision supporting, risk prediction, resource management, public health, disease prevention, and so on. That makes more efficient use of medical resources and promotes human health.

參考文獻


7Andreu-Perez J, Poon CCY, Merrifield RD, et al: Big data for health. IEEE J Biomed Health Inform 2015; 19:1193-208.
Fang R, Pouyanfar S, Yang Y, et al: Computational health informatics in the big data age: a survey. ACM Comput Surv 2016;49:12.
Huang HH, Lee CC, Chen HH: Mining professional knowledge from medical records. In: Brain Inform Health. Springer 2014;152-63.
Goldstein BA, Navar AM, Pencina MJ, et al: Opportunities and challenges in developing risk prediction models with electronic health records data: a systematic review. J Am Med Inform Assoc 2016 May 17. pii: ocw042.
Hong KJ, Shin SD, Ro YS, et al: Development and validation of the excess mortality ratio-based Emergency Severity Index. Am J Emerg Med 2012;30:1491-500.

被引用紀錄


陳明郁、樊祖燁、陳姳孜、韋智皓(2023)。醫護用品包交易平臺行銷企劃之研究管理資訊計算12(1),117-130。https://doi.org/10.6285/MIC.202303_12(1).0010
張彩秀、劉筱茜、李玲玲、林雲萍、謝美慧、李逸、劉影梅、陳靜敏、王秀紅、蔡秀敏(2022)。台灣公共衛生護理人員前瞻性專業能力省思護理雜誌69(2),89-96。https://doi.org/10.6224/JN.202204_69(2).11

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