Jillian Parker on Muck Rack

Jillian Parker

Rochester
As seen in: Medium, SAGE Publishing, ACS Publications, Cell Press, Spectrum News Rochester, Spectrum News 13, KSFY-TV (Sioux Falls, SD), Bay News 9, The Journal of Biological Chemistry, KSNB-TV (Hastings, NE) and
| Former Morning Reporter (still catching up on sleep) | Healthcare Public Relations | Jersey Raised | Yankees | Tweets are my own |
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Articles

Cat

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By Jillian Parker
| Medium
I don’t even have a name. You let me waste away in this empty apartment with buckets of champagne. You sleep through the day and wake in a haze from dreaming about your life. You could have had it your way. I sift through the crowds. Music entirely too loud. A fly on the wall. Watching you bat away their hands. But I’ve been here all along. The first to hear your songs about the moon and the trees and the river that’s so long. So pull down your mask close your eyes again.
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AI-readiness for Biomedical Data: Bridge2AI Recommendations

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By Timothy Clark, Harry Caufield, Jillian Parker, Sadnan Al Manir
| biorxiv.org
Abstract Biomedical research and clinical practice are in the midst of a transition toward significantly increased use of artificial intelligence (AI) and machine learning (ML) methods. These advances promise to enable qualitatively deeper insight into complex challenges formerly beyond the reach of analytic methods and human intuition while placing increased demands on ethical and explainable artificial intelligence (XAI), given the opaque nature of many deep learning methods.
Open in Who Shared Issue with article?

AI-readiness for Biomedical Data: Bridge2AI Recommendations

|
By Timothy Clark, Harry Caufield, Jillian Parker, Sadnan Al Manir
| biorxiv.org
Abstract Biomedical research and clinical practice are in the midst of a transition toward significantly increased use of artificial intelligence (AI) and machine learning (ML) methods. These advances promise to enable qualitatively deeper insight into complex challenges formerly beyond the reach of analytic methods and human intuition while placing increased demands on ethical and explainable artificial intelligence (XAI), given the opaque nature of many deep learning methods.
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