Interactive Web Application for Plotting Personalized Prognosis Prediction Curves in Allogeneic Hematopoietic Cell Transplantation Using Machine Learning.
Journal:
Transplantation
Published Date:
May 1, 2021
Abstract
BACKGROUND: Allogeneic hematopoietic cell transplantation (allo-HCT) is a curative treatment option for malignant hematological disorders. Transplant clinicians estimate patient-specific prognosis empirically in clinical practice based on previous studies on similar patients. However, this approach does not provide objective data. The present study primarily aimed to develop a tool capable of providing accurate personalized prognosis prediction after allo-HCT in an objective manner.
Authors
Keywords
Adolescent
Adult
Aged
Cause of Death
Computer Graphics
Decision Support Techniques
Disease Progression
Female
Hematopoietic Stem Cell Transplantation
Humans
Internet
Machine Learning
Male
Middle Aged
Predictive Value of Tests
Progression-Free Survival
Recurrence
Retrospective Studies
Risk Assessment
Risk Factors
Time Factors
Transplantation, Homologous
Young Adult