解聰元:Big data and medicine

Martin Hisboeck 解博士目前在Geber Brand Consulting 工作、曾在台大EMBA91畢業. 也是師大中文系博碩士、维也纳大學中文畢

今天介紹他對big data 在医療的應用

big data - patience, fitness, insurance, outbreak, genetic, social media (outbreak disease data, 大流行暴發的疾病資料)

sensors- batteryless power source, nanosensors, parathyroid hormone microchip injector, google lens,

patience data source, compare n analysis, develop models, preventative預付性 medicines一So cost down due to data use and prevention

sensor data source, procession in device, analysis by algorithm, sustainabilty by system methodology

癌症診斷、lBM電腦可以比對1億筆DNA病人資料、但人脑則受限經驗、大数据的价值在於fast, efficient, correct, cheaper to diagnosis

brain tumor, Siemens can detect it by imagines

robotic medicine, create blueprint for automated surgeries. most surgeries are repeated, 很多手術都是重複的_医生花很多時間重複做類似的事

biggest trend in 2016
data visulization,
cloud based solution
privacy, security, capacity
data collection iot
digitalization of patient record

台灣健保、付費给藥fee for services, 但未來应該看结果给付outcome based

chronic renal failure and cancer have the highest outpatient cost 45 n 33 % of NHI  and 30% of inpatient , it can be greatly reduced in big data solutions.

台灣問題、各自為政、不会用數據來降成本、浪費、老人、医护过勞而没時間不关心病人、漸多的NCD(三大cancer, cardio, cerebral vascular disease 占45%)_所有NCD 則占79%死亡

他的linkedin
http://www.linkedin.com/in/hiesboeck