A Systematic Review of Machine Learning Techniques in Hematopoietic Stem Cell Transplantation (HSCT).

ABSTRACT: Machine learning techniques are widely used nowadays in the healthcare domain for the diagnosis, prognosis, and treatment of diseases. These techniques have applications in the field of hematopoietic cell transplantation (HCT), which is a potentially curative therapy for hematological malignancies. Herein, a systematic review of the application of machine learning (ML) techniques in the HCT setting was conducted. We examined the type of data streams included, specific ML techniques used, and type of clinical outcomes measured. A systematic review of English articles using PubMed, Scopus, Web of Science, and IEEE Xplore databases was performed. Search terms included "hematopoietic cell transplantation (HCT)," "autologous HCT," "allogeneic HCT," "machine learning," and "artificial intelligen

SUBMITTER: Gupta V 

PROVIDER: S-EPMC7663237 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature