Events Calendar

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12:00 AM - TEDMED 2017
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Raleigh Health IT Summit
2017-10-19 - 2017-10-20    
All Day
About Health IT Summits Renowned leaders in U.S. and North American healthcare gather throughout the year to present important information and share insights at the Healthcare [...]
Connected Health Conference 2017
2017-10-25 - 2017-10-27    
All Day
The Connected Life Journey Shaping health and wellness for every generation. Top-rated content Valued perspectives from providers, payers, pharma and patients Unmatched networking with key [...]
TEDMED 2017
2017-11-01 - 2017-11-03    
All Day
A healthy society is everyone’s business. That’s why TEDMED speakers are thought leaders and accomplished individuals from every sector of society, both inside and outside [...]
AMIA 2017 Annual Symposium
2017-11-04 - 2017-11-08    
All Day
Call for Participation We invite you to contribute your best work for presentation at the AMIA Annual Symposium – the foremost symposium for the science [...]
Events on 2017-10-19
Raleigh Health IT Summit
19 Oct 17
Raleigh
Events on 2017-10-25
Events on 2017-11-01
TEDMED 2017
1 Nov 17
La Quinta
Events on 2017-11-04
AMIA 2017 Annual Symposium
4 Nov 17
WASHINGTON
Articles

Microsoft, 16 health systems shape AI

Sixteen health systems, in collaboration with Microsoft and other healthcare technology organizations, have established the Trustworthy & Responsible AI Network (TRAIN). This initiative focuses on defining best practices and standards for AI in healthcare to improve the quality and trustworthiness of AI applications. TRAIN aims to ensure responsible development and evaluation standards for technologies like patient screening and administrative task automation. Major health systems including Mercy, Mass General Brigham, Providence, Cleveland Clinic, and AdventHealth are part of TRAIN, along with partners OCHIN and TruBridge. The goal is to make TRAIN’s benefits accessible to organizations of all sizes. Founding members of TRAIN were also part of the Coalition for Health AI (CHAI), and TRAIN will build upon CHAI’s work to operationalize principles for trustworthy healthcare AI.