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Yuqing Qiu

Research Statistician

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Yuqing is an experienced research biostatistician working at Weill Cornell Medicine. She has seven years of working experience in statistics field. She collaborates with a variety of medical departments for biomedical research studies. She is proficient in the application of traditional biostatistical methods and state-of-the-art data science tools, including but not limited to longitudinal data analysis, survival analysis, missing data management, machine learning predictions, causal inference, and study and experiment design. 

COVID-19 Research

Yuqing collaborates with Pathology and Laboratory Medicine department in Weill Cornell Medicine for COVID research studies started April 2020, as soon as she can, to disperately help as the world descends into chaos. The team evaluates diagnosis tools, investigates the antibody response for both COVID patients and vaccine receipients, explore the association between antibody level and mortality, and analyze administrative data to assist medical resouce allocation.

Published Papers
  • Performance Evaluation of the MatMaCorp COVID-19 2SF Assay for the Detection of SARS-CoV-2 from Nasopharyngeal Swabs (American Society for Microbiology)

  • Rapid detection of SARS-CoV-2 variants of concern by single nucleotide polymorphism genotpying using TaqMan assays (Diagnostic Microbiology & Infectious Disease)

The Impact of COVID-19 on Physician-Scientist Trainees and Faculty in the United States: A National Survey (Academic Medicine) Rotational Thromboelastometry (ROTEM) in Patients with Acute Respiratory Distress Syndrome (ARDS) due to Coronavirus Disease 2019 (COVID-19): Is There a Viscoelastic Fingerprint and a Role for Predicting Thrombosis? (Surgery)

Policy Evaluation Studies in Urology and Gynecology

This project evaluates the real-world effect of the FDA regulations and research publications on methods through surgical treatments in Urology and Gynecology field. We assess the application of investigated methods in real world overtime and determine how these applications were affected by the regulations and/or publications. This project advocates the application of the proved-effective methods and warn the use of treatment with worse disease-free and overall survival after the finding of adverse effects.

Published Papers

Minimal Clinically Important Difference for Upper Extremity Patients

This research project explored and provided benchmark for examining treatment effect for upper extremity surgery. Our calculation considers patients’ self-reported outcome and provides anchor-based minimal clinically important difference (MCID) estimates. Our calculation supports future research to examine whether the treatments have clinically significant effect by helping the interpretation of clinical outcome scores and in sample size estimation for clinical studies to efficiently allocate medical resource.

Published Papers
  • The minimal clinically important difference of the Patient-Reported Outcomes Measurement Information System (PROMIS) physical function and upper extremity computer adaptive tests and QuickDASH in the setting of elbow trauma (JSES International)

  • The minimal clinically important difference of the Patient-Reported Outcomes Measurement Information System (PROMIS) physical function and upper extremity computer adaptive tests and QuickDASH in the setting of elbow trauma (JSES International)

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