Literature DB >> 33153901

Artificial intelligence meets hematology.

Lars Kaestner1.   

Abstract

The application of artificial intelligence (AI) in hematology it not new at all. However, it increasingly becomes part of the measurement of hematological parameters and subsequently also influences decision making. Here some examples are provided where well established parameters could be exploited better, if data are not reduced to single values but instead the entire data generation process is considered. Furthermore applications of artificial neural networks (ANN), point of care (PoC) devices and the internet of things (IoT) are discussed. Beside all the technical advancements human judgement will remain the last decision.
Copyright © 2020 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Artificial neural network; Red blood cells; Theragnostics

Mesh:

Year:  2020        PMID: 33153901     DOI: 10.1016/j.transci.2020.102986

Source DB:  PubMed          Journal:  Transfus Apher Sci        ISSN: 1473-0502            Impact factor:   1.764


  2 in total

1.  Continuous Percoll Gradient Centrifugation of Erythrocytes-Explanation of Cellular Bands and Compromised Age Separation.

Authors:  Felix Maurer; Thomas John; Asya Makhro; Anna Bogdanova; Giampaolo Minetti; Christian Wagner; Lars Kaestner
Journal:  Cells       Date:  2022-04-11       Impact factor: 7.666

Review 2.  A Review of Artificial Intelligence Applications in Hematology Management: Current Practices and Future Prospects.

Authors:  Yousra El Alaoui; Adel Elomri; Marwa Qaraqe; Regina Padmanabhan; Ruba Yasin Taha; Halima El Omri; Abdelfatteh El Omri; Omar Aboumarzouk
Journal:  J Med Internet Res       Date:  2022-07-12       Impact factor: 7.076

  2 in total

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