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DTSTART;TZID=America/New_York:20210625T130000
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UID:5427-1624626000-1624629600@impactcollaboratory.org
SUMMARY:Inclusion of Diverse Participants in Pragmatic Clinical Trials: Meeting Participants Where They Are – Outreach\, Trust\, and Consent to Maximize Diversity
DESCRIPTION:Guest Moderator:\nEmily O’Brien\, PhD\nAssociate Professor\, Department of Population Health Sciences\nDuke Clinical Research Institute\nDuke University School of Medicine \nPanel:\nJonathan Jackson\, PhD\nExecutive Director\nCommunity Access\, Recruitment\, and Engagement (CARE) Research Center\nMassachusetts General Hospital and Harvard Medical School \nJudith Schlaeger\, PhD\, CNM\, LAc\, FAAN\nAssociate Professor\, Department of Human Development Nursing Science\nUniversity of Illinois Chicago \nStacy Sterling\, DrPH\, MSW\, MPH\nResearch Scientist\nKaiser Permanente Division of Research\, Northern California \nTopic: Inclusion of Diverse Participants in Pragmatic Clinical Trials: Meeting Participants Where They Are – Outreach\, Trust\, and Consent to Maximize Diversity\nDate: Friday\, June 25\, 2021\, 1:00-2:00 p.m. ET \nMeeting Info: To check whether you have the appropriate players installed for UCF (Universal Communications Format) rich media files\, go to https://dukemed.webex.com/dukemed/systemdiagnosis.php. \nTo join the online meeting:\nGo to https://dukemed.webex.com/dukemed/j.php?MTID=m228b52a4666c1e24046e11c01ae7bd0d
URL:https://impactcollaboratory.org/event/inclusion-of-diverse-participants-in-pragmatic-clinical-trials-meeting-participants-where-they-are-outreach-trust-and-consent-to-maximize-diversity/
CATEGORIES:interest
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DTSTART;TZID=America/New_York:20210625T130000
DTEND;TZID=America/New_York:20210625T160000
DTSTAMP:20260609T175924
CREATED:20210617T215125Z
LAST-MODIFIED:20210623T165409Z
UID:5807-1624626000-1624636800@impactcollaboratory.org
SUMMARY:Virtual Forum: Artificial Intelligence/Machine Learning (AI/ML) Consortium to Advance Health Equity and Researcher Diversity (AIM-AHEAD)
DESCRIPTION:The Artificial Intelligence/Machine Learning (AI/ML) Consortium to Advance Health Equity and Researcher Diversity (AIM-AHEAD) virtual forum will occur on Friday\, June 25th (1:00-4:00 PM EDT). This virtual forum aims to bring together stakeholders across academia\, federal agencies\, the data science/tech industry\, and health care systems and centers who are interested in leveraging artificial intelligence and machine learning (AI/ML) for research\, with a primary focus on mitigating health disparities.  The purpose of this meeting will be to provide an overview of the initiative approved for funding by NIH and then engage attendees in listening sessions via breakout groups which will focused on three main topics: research interests\, computing infrastructure and resources\, and training needs. The meeting will conclude with a report back from these smaller breakout discussions and a final summary of the forum discussion and anticipated next steps.  The feedback from this event will inform the establishment of mutually beneficial and  coordinated partnerships to increase the participation and representation of researchers and communities currently underrepresented in the development of AI/ML models and enhance the capabilities of this emerging technology\, beginning with EHR data.  \n  \nRegistration Closed: Due to the enthusiastic response\, the AIM-AHEAD Team have reached the participation limit to ensure meaningful conversation\, so they have closed registration.  Over the next several weeks\, they will have additional opportunities for people to provide feedback and ask questions\, including a formal Request for Information (RFI) to gather written comments.  They will also post a meeting summary of this stakeholder forum. If you have any questions about this event\, please contact AIM-AHEAD@od.nih.gov. 
URL:https://impactcollaboratory.org/event/virtual-forum-artificial-intelligence-machine-learning-ai-ml-consortium-to-advance-health-equity-and-researcher-diversity-aim-ahead/
LOCATION:https://www.niddk.nih.gov/news/meetings-workshops/2021/artificial-intelligence-machine-learning-consortium
CATEGORIES:interest
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