Events Calendar

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AACP Annual Meeting
2015-07-11 - 2015-07-15    
All Day
The AACP Annual Meeting is the largest gathering of academic pharmacy administrators, faculty and staff, and each year offers 70 or more educational programs that cut across [...]
Engage, Innovation in Patient Engagement
2015-07-14 - 2015-07-15    
All Day
MedCity ENGAGE is an executive-level event where the industry’s brightest minds and leading organizations discuss best-in-class approaches to advance patient engagement and healthcare delivery. ENGAGE is the [...]
mHealth + Telehealth World 2015
2015-07-20 - 2015-07-22    
All Day
The role of technology in health care is growing year after year. Join us at mHealth + Telehealth World 2015 to learn strategies to keep [...]
2015 OSEHRA Open Source Summit
2015-07-29 - 2015-07-31    
All Day
Join the Premier Open Source Health IT Summit! Looking to gain expertise in both public and private sector open source health IT?  Want to collaborate [...]
Events on 2015-07-11
AACP Annual Meeting
11 Jul 15
National Harbor, Maryland
Events on 2015-07-14
Events on 2015-07-20
Events on 2015-07-29
2015 OSEHRA Open Source Summit
29 Jul 15
Bethesda
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.