11月 15

Healthcare Roundtable: Big Data & AI in Healthcare – Experiences in kidney disease

Location

在日ドイツ商工会議所

〒102-0075
東京都千代田区三番町2-4 三番町KSビル5階 (東京都)

Details
Event Start
2019/11/15 | 08:30
Event End
2019/11/15 | 10:30
Price
無料
Event Language
英語
Registration
Subscription Date
2019/11/14

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イベントについて:

Healthcare systems are under pressure to deliver more and better care with limited resources. At the same time, Health care is entering a new era where the advent of “big data” and artificial intelligence bring tremendous opportunities to revolutionize the profession. In order to guide the development of new digital technologies like AI at an acceptable scale, alignment of policies and regulations is essential to ensure effective integration of AI in healthcare delivery. In order to be purposeful, data must be analyzed, interpreted and used to improve patient care. As the leading provider of dialysis products and services, Fresenius Medical Care has operationalized a suite of more than 20 machine and deep learning algorithms in clinical and operational needs to the benefit of patients, payors and the healthcare system in North America and will share experiences of its journey in AI in chronic kidney disease.

スピーカーについて:

Len Usvyat is a Vice President of Applied Advanced Analytics with Fresenius Medical Care’s Global Medical Office. Len holds a Master’s Degree from the University of Pennsylvania and PhD from the University of Maastricht in Netherlands. He has over 15 years of experience in traditional and advanced data analytics, research, and epidemiology. He is responsible for supporting analytical efforts for Fresenius’s integrated care assets such as its pharmacy, vascular care centers, urgent care facilities, and the Fresenius health plan. Globally, Len is responsible for connecting various advanced analytics partners inside and outside Fresenius Medical Care to the Medical Office Clinical Agenda and building out FMC’s capabilities in applied advanced analytics endeavors. These efforts vary and include activities such as AI-based data driven efforts, routine and custom reporting, predictive modeling, outcomes analysis, and research. Len has published over 60 manuscripts in peer reviewed journals.

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