From demand forecasting to inventory ordering decisions for red blood cells through integrating machine learning, statistical modeling, and inventory optimization-Reference-Cited by-同舟云学术

From demand forecasting to inventory ordering decisions for red blood cells through integrating machine learning, statistical modeling, and inventory optimization

Published:2021-11-16 Issue:1 Volume:62 Page:87-99
ISSN:0041-1132
Container-title:Transfusion
language:en
Short-container-title:Transfusion

Author:

Li Na¹²³^ORCID,Arnold Donald M.²⁴⁵^ORCID,Down Douglas G.³,Barty Rebecca²⁶^ORCID,Blake John⁴⁷^ORCID,Chiang Fei³,Courtney Tom⁴,Waito Marianne⁴,Trifunov Rick⁴,Heddle Nancy M.²⁴^ORCID

Affiliation:

1. Department of Community Health Sciences University of Calgary Calgary Alberta Canada

2. McMaster Centre for Transfusion Research, Department of Medicine McMaster University Hamilton Ontario Canada

3. Department of Computing and Software McMaster University Hamilton Ontario Canada

4. Centre for Innovation, Integrated Supply Chain and Analytics Canadian Blood Services Ottawa Ontario Canada

5. Department of Medicine, Michael G. DeGroote School of Medicine McMaster University Hamilton Ontario Canada

6. Southwest Region Ontario Regional Blood Coordinating Network Hamilton Ontario Canada

7. Department of Industrial Engineering Dalhousie University Halifax Nova Scotia Canada

Funder

Canadian Blood Services

Mitacs

Publisher

Wiley

Subject

Hematology,Immunology,Immunology and Allergy

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/trf.16739

Reference52 articles.

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4. Review of current transfusion therapy and blood banking practices

5. Platelet Transfusion: A Clinical Practice Guideline From the AABB

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