The LHS Collaboratory is a hub for advancing interdisciplinary research and development of learning health systems at the University of Michigan. Joan’s poster presentation was to convey how MiCHAMP can contribute to that mission. You can view the poster here: https://umich.box.com/v/LHS-Collaboratory
Register now for FFMI Symposium: Exploring the Singularity in Healthcare: Digital Innovation for IMPACT
Join Fast Forward Medical Innovation for an exclusive health IT symposium to learn about the growing and inevitable intersection of technology and healthcare, along with research/innovation/commercialization opportunities in the arena of digital health and “big data”. This half-day event is designed to educate faculty, staff, students, and community on how digital tools, precision health, and machine learning algorithms will change…Details
University of Michigan’s Institute for Healthcare Policy and Innovation (IHPI) recently released their digital annual report. http://ihpiannualreport.med.umich.edu/ MiCHAMP members Karandeep Singh and Akbar Waljee Discuss Precision Health in IHPI Annual Report: https://www.youtube.com/watch?v=E8DYNvpkZUYDetails
A specific type of blood thinner may be a safer choice for reducing stroke risk in those who have both end-stage kidney disease and atrial fibrillation.
The Michigan Institute for Data Science (MIDAS) will host the Women in Big Data at Michigan Symposium on November 12th, 8:30 AM – 4:30 PM at the Michigan League. For more information and to register to attend, visit the MIDAS website
The Machine Learning for Healthcare Conference (MLHC) will be hosted by the University of Michigan August 8-10, 2019. MLHC is an annual research meeting that exists to bring together two usually insular disciplines: computer scientists with artificial intelligence, machine learning, and big data expertise, and clinicians/medical researchers. This year’s conference will be held at Stanford…Details
Artificial intelligence, which is bringing us everything from self-driving cars to personalized ads on the web, is also invading the world of medicine.
Two researchers are developing data-driven tools to improve the detection of serious heart conditions Heart failure and atrial fibrillation (AF) are two common chronic conditions that can be managed if recognized early, but can have deadly consequences if they go undetected.Details
As more people use artificial intelligence, they will need tools that detect unfairness in the underlying algorithms.