In this Friday’s PCT Grand Rounds, Michael Pencina of Duke University will present “Public-Private Partnerships in the Trustworthy Health AI Ecosystem.”
The Grand Rounds session will be held on Friday, March 8, 2024, at 1:00 pm eastern.
Pencina is a professor of biostatistics and bioinformatics and the vice dean for data science in the Duke University School of Medicine. He is the director of the university’s Duke AI Health initiative and the chief data scientist for Duke Health.
In this Friday’s PCT Grand Rounds, Eric Perakslis of Duke University will present “AI & ML: Want to Play a Game?”
The Grand Rounds session will be held on Friday, August 4, 2023, at 1:00 pm eastern.
Perakslis is a professor in population health sciences and the chief research technology strategist in the Duke University School of Medicine.
In a guest editorial in the American Journal of Bioethics, members of the NIH Pragmatic Trials Collaboratory’s Ethics and Regulatory Core introduced the issue’s target article and peer commentaries on artificial intelligence and machine learning in healthcare. Prof. Kayte Spector-Bagdady and Drs. Vasiliki Rahimzadeh and Kaitlyn Jaffe, who are Core members, were joined by coauthor Dr. Jonathan Moreno in writing the editorial.The target article of the themed collection proposes a research ethics framework for the clinical translation of healthcare machine learning. In several peer commentaries accompanying the article, experts offer their perspectives on the proposed framework, including critiques of “the insufficiency of current ethics and regulatory solutions to adequately protect communities at higher risk for [machine learning] bias.”
Read the full editorial, “Promoting Ethical Deployment of Artificial Intelligence and Machine Learning in Healthcare.” Learn more about our Ethics and Regulatory Core.
Erich S. Huang, MD, PhD
Co-Director, Duke Forge
Departments of Biostatistics & Bioinformatics and Surgery
Duke University School of Medicine
In Dreams Begin Responsibilities: Data Science as a Service—Using AI to Risk Stratify a Medicare Population and Build a Culture
Data science; Data liquidity; Data standards; Machine learning; Duke Forge; Application programming interface; Artificial intelligence
If we’re trying to build an ecosystem, then the electronic health record (EHR) platform needs to be evaluated by whether it is truly participatory in this ecosystem. If not, then its deficiencies must be remediated.
The faster we can move to the cloud and use building blocks that “snap” together, the faster we can get answers. We want to be building applications instead of infrastructure.
Algorithms don’t have ethics; some have hidden biases. Algorithms need to be scrutinized and tested for such biases. They also must be secured so they cannot be manipulated.
Read more about Duke Forge and check out articles on the blog.
Tags
#pctGR, @Collaboratory1, @DukeForge
