ISSN: 1300-7777 E-ISSN: 1308-5263
Artificial Intelligence approaches in hematopoietic cell transplant: A review of the current status and future directions [Turk J Hematol]
Turk J Hematol. Ahead of Print: TJH-79999 | DOI: 10.4274/tjh.2018.0123  

Artificial Intelligence approaches in hematopoietic cell transplant: A review of the current status and future directions

Ibrahim N. Muhsen1, Tusneem Elhassan2, Shahrukh K. Hashmi3
1College of Medicine, Alfaisal University, Riyadh, KSA
2Oncology Center, King Faisal Specialist Hospital and Research Center, Riyadh, KSA
3Oncology Center, King Faisal Specialist Hospital and Research Center, Riyadh, KSA; Division of Hematology, Department of Medicine, Mayo Clinic, Rochester, MN, USA

Currently, the evidence-based literature on healthcare is expanding exponentially. The opportunities provided by the advancement in artificial intelligence (AI) tools i.e. machine learning are appealing in tackling many of the current healthcare challenges. Thus, AI integration is expanding in most fields of healthcare, including the field of hematology. This study aims to review the current applications of AI in the field hematopoietic cell transplant (HCT). Literature search was done involving the following databases: Ovid-Medline including in-Process and Other Non-Indexed Citations and google scholar. The abstracts of the following professional societies: American Society of Haematology (ASH), American Society for Blood and Marrow Transplantation (ASBMT) and European Society for Blood and Marrow Transplantation (EBMT) were also screened. Literature review showed that the integration of AI in the field of HCT has grown remarkably in the last decade and confers promising avenues in diagnosis and prognosis within HCT populations targeting both pre and post-transplant challenges. Studies on AI integration in HCT have many limitations that include poorly tested algorithms, lack of generalizability and limited use of different AI tools. Machine learning techniques in HCT is an intense area of research that needs a lot of development and needs extensive support from hematology and HCT societies / organizations globally since we believe that this would be the future practice paradigm.

Keywords: Artificial intelligence, machine learning, hematopoietic cell transplant




Corresponding Author: Shahrukh K. Hashmi, Türkiye


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Impact Factor (2016) = 0.686