Events Calendar

09 Dec
Machine Learning to Determine Dynamically Evolving New-Onset Venous Thromboembolic (VTE) Event Risk
Event Type

Defenses

Target Audience

Faculty, Graduate Students

University Unit
School of Nursing: Office of the Dean
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Machine Learning to Determine Dynamically Evolving New-Onset Venous Thromboembolic (VTE) Event Risk

This is a past event.

 in Hospitalized Patients

Tiffany Purcell Pellathy will present her PhD dissertation titled, “Machine Learning to Determine Dynamically Evolving New-Onset Venous Thromboembolic (VTE) Event Risk in Hospitalized Patients", with committee Marilyn Hravnak (chair), Salah Al-Zaiti, Giles Clermont, Artur Dubrawski, Young Ji Lee, Michael Pinsky and Melissa Saul.

Zoom link is provided after ticket registration. 

Dial-In Information

Register for event to receive Zoom URL.

Wednesday, December 9 at 3:00 p.m. to 5:00 p.m.

Virtual Event

Machine Learning to Determine Dynamically Evolving New-Onset Venous Thromboembolic (VTE) Event Risk

 in Hospitalized Patients

Tiffany Purcell Pellathy will present her PhD dissertation titled, “Machine Learning to Determine Dynamically Evolving New-Onset Venous Thromboembolic (VTE) Event Risk in Hospitalized Patients", with committee Marilyn Hravnak (chair), Salah Al-Zaiti, Giles Clermont, Artur Dubrawski, Young Ji Lee, Michael Pinsky and Melissa Saul.

Zoom link is provided after ticket registration. 

Dial-In Information

Register for event to receive Zoom URL.

Wednesday, December 9 at 3:00 p.m. to 5:00 p.m.

Virtual Event

Event Type

Defenses

Target Audience

Faculty, Graduate Students

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