Health Services, Systems and Policy Seminar Series: David Wiljer

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Learning to Adapt and Care Compassionately in the World of Data and Artificial Profile of David WiljerIntelligence

Dr. David Wiljer, UHN, IHPME

Dr. David Wiljer is a member of the community providing groundbreaking perspectives and inspiring contributions to digital health policy, management, education and evaluation. He is the Executive Director of Education, Technology & Innovation at the University Health Network, and former Senior Director of Transformational Education and Academic Advancement at CAMH. David is also an Associate Professor in the Department of Psychiatry, Faculty of Medicine and the Institute of Health Policy Management and Evaluation at the University of Toronto. He is a former President of the American Association of Cancer Education, and the current Chair of the Scholarship Committee for the Society for Academic Continuing Medical Education. Dr. Wiljer has led research and development projects that focus on putting knowledge into action by utilizing health information technologies and knowledge management approaches to promote lifelong learning and CPD. Through his research and scholarship, he also explores the impact of digital technologies on patient partnerships and on high quality care.


Approaching the Promise of Artificial Intelligence & Big Data in Healthcare

Health systems, services and policy researchers are increasingly interested in the potential for AI and Big Data to address challenges ranging from complex societal problems to those relating to individual care.

For this reason, the Health Services, Systems & Policy Seminar Series at the Institute of Health Policy, Management and Evaluation (IHPME), University of Toronto will focus this year on the potential and limitations of AI and Big Data to improve healthcare.

Canadian and international researchers and practitioners from an array of disciplines including computer science, decision sciences, predictive analytics, and bioinformatics will join us to discuss applications of AI and big data to issues ranging from genomics, radiology, public health and hospital scheduling to blood transfusion.

Please consider forwarding this information to any colleagues who might be interested.

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