醫療大數據及其應用

Big Health Data and Its Applications

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。

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.