Shengpu Tang on Muck Rack

Shengpu Tang

As seen in: Nature
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Articles

Clinical trials for continuously monitored and updated AI systems

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By Wouter van Amsterdam, Michael Oberst, Jean Feng, Jenna Wiens, Shengpu Tang, Shalmali Joshi, Rajesh Ranganath, Mark Sendak, Uri Shalit, Julia Vogt, Brett Beaulieu-Jones, Muhammad Mamdani, Patrick J. Heagerty, Thomas Fleming, Anna Goldenberg 
| Nature
As artificial intelligence becomes embedded in clinical workflows, trials must accommodate ongoing monitoring and updates.
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Early identification of patients admitted to hospital for covid-19 at risk of clinical deterioration: model development and multisite external validation study

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By Fahad Kamran, Shengpu Tang, Erkin Otles, Dustin McEvoy
| bmj.com
Research Early identification...
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Evaluating a Widely Implemented Proprietary Deterioration Index Model Among Hospitalized COVID-19 Patients

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By Karandeep Singh , Thomas S. Valley, Shengpu Tang, Benjamin Li
| medRxiv
Abstract Introduction: The Epic Deterioration Index (EDI) is a proprietary prediction model implemented in over 100 U.S. hospitals that was widely used to support medical decision-making during the COVID-19 pandemic. The EDI has not been independently evaluated, and other proprietary models have been shown to be biased against vulnerable populations. Methods: We studied adult patients admitted with COVID-19 to non-ICU care at a large academic medical center from March 9 through May 20, 2020.
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