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: Automated Machine Learning (AutoML) Algorithms to Predict Post-Operative Venous Thromboembolism (VTE) Using the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) Database

Researchers

Presenter

  • Avinash Thangirala

Principal Investigators

  • Yindalon Aphinyanaphongs

  • Ji Chen

  • Jacob A Martin

  • Usman Alam

  • Nehal Dhaduk

  • Andrew C Kelleher

  • Jake F Oeding

  • Eric Hu

  • Nicolai Ostberg

  • Gregory Katz

  • Shelly Brejt

  • Karen C Kan

Medical Centers

  • NEW YORK UNIVERSITTY, New York, NY

  • AIG, New York, NY

  • New York Univ Langone Health, New York, NY

Locations

  • United States

Companies

  • N/A

Study Components

Therapeutic Area

  • Cardiovascular (CVS)

  • Pulmonary/Respiratory Diseases

  • Blood/haematological Diseases

Disease

  • Venous thrombosis

  • Deep vein thrombosis

  • Pulmonary embolism

Biomarkers

  • N/A

Drug/Treatment

  • N/A

Outcome

  • N/A

Study Design

  • N/A

Phase

  • N/A

Study Id's

  • N/A

Sponsors

  • N/A

Result

  • N/A

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