Applied Artificial Intelligence and Machine Learning

Education

Healthcare is at an inflection point. Machine learning and data science are becoming key components in developing AI to support predictive and preventative insights. See how these insights are enabling global health leaders like Cerner, Geisinger, GYANT, and BenevolentAI to accelerate value based care.
This session explores how to build ethical considerations into machine learning projects and tools. Having an ethical framework will help to provide transparency and build public trust.
The democratization of artificial intelligence (AI) in healthcare, which is being driven by cloud technologies, is leading to greater access and more predictive work in patient monitoring and smarter reactive responses to health issues.

General Education

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Speakers

Philip Held
Research DirectorRush University Medical Center
Jane Griffiths
Chief Nursing Information OfficerDubai Health Authority
Diana McKenzie
Partner and Chair, IT and OutsourcingHuntermaclean Law Firm
Wade Schulz
Assistant Professor, Dir of InformaticsLab Med, Yale School of Medicine
Marc Overhage
Chief Medical informatics Officer & VP intelligence StrategyCerner Corporation