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2404 : Machine Learning Methods to Better Predict Post-Hematopoietic Stem Cell Transplant (HSCT) Leukemic Relapse in Pediatric Patients with Acute Lymphoblastic Leukemia: Random Forest (RF) Classification Featuring Serial Post-Transplant Lineage-Specific Chimerism

Researchers

Presenter

  • David C Shyr

Principal Investigators

  • Bing Melody Zhang

  • Robertson Parkman

  • Simon E. Brewer

Medical Centers

  • Department of Dermatology, Stanford University, Palo Alto, CA

  • Division of Stem Cell Transplantation and Regenerative Medicine, Department of Pediatrics, Stanford School of Medicine, Stanford, CA

  • University of Utah, Salt Lake City, UT

Locations

  • United States

Companies

  • N/A

Study Components

Therapeutic Area

  • Oncology (ONC)

Disease

  • Acute lymphoblastic leukemia

  • Hematological malignancies

Biomarkers

  • Breakpoint Cluster Region

  • Cluster of Differentiation 2AP

  • Cluster of Differentiation 34

Drug/Treatment

  • N/A

Outcome

  • N/A

Study Design

  • Cohort

Phase

  • NA

Study Id's

  • N/A

Sponsors

  • N/A

Result

  • N/A

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