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Artificial Intelligence

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By ST Engineering | 10:47 pm | August 06, 2024
AI has permeated various aspects of daily life in recent years, but its impact on healthcare has been hailed as revolutionary.
By Adam Ang | 10:14 pm | August 06, 2024
Encryption technology used in elections can potentially improve an AI model's predictive capability without compromising patient data privacy.
By Andrea Fox | 11:48 am | August 06, 2024
Offered in partnership with Novo Nordisk Foundation, the fellowship will focus on technologies that analyze vast amounts of data to increase diagnostic accuracy, speed personalized medicine and improve clinical trials.
By Bill Siwicki | 12:52 pm | August 05, 2024
The Boston health system's director of AI operations discusses some challenges and best practices for integrating large language models into research and operational tasks while explicitly excluding direct clinical care.
By Nathan Eddy | 11:33 am | August 05, 2024
Prolonged understaffing in clinical laboratories threatens to compromise patient care, but deployment of automation and artificial intelligence technologies could offer a lifeline to burned out lab workers.
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By AIRS Medical | HIMSS TV | 07:53 am | August 05, 2024
Jayden Jung, head of business development at AIRS Medical, discusses SwiftMR, the company's AI-powered product that shortens MRI scan times by an average of 40% without sacrificing image quality so hospitals can scan 30% more patients.
By Bill Siwicki | 09:00 am | August 02, 2024
A comprehensive look at the market by Shahab Vagefi, managing director in Thomas H. Lee Partners' healthcare vertical who specializes in healthcare information technology.
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By HIMSS TV | 07:00 am | August 02, 2024
AI-powered radiology tools aren't yet ready to make diagnoses; they must return accurate results and save time to be truly useful to burned-out radiologists, says Dr. Benoit Desjardins, University of Pennsylvania radiology professor.
By Mike Miliard | 05:52 pm | August 01, 2024
The freely-downloadable tool, called Dioptra, is designed to help artificial intelligence developers understand some unique data risks with AI models, and help them "mitigate those risks while supporting innovation," says NIST's director.