Literature DB >> 29790152

Machine learning algorithms for accurate differential diagnosis of lymphocytosis based on cell population data.

Laura Bigorra1,2, Iciar Larriba1, Ricardo Gutiérrez-Gallego2.   

Abstract

Entities:  

Keywords:  cell population data; chronic lymphocytic leukaemia; lymphocytosis; machine learning algorithms; reactive lymphocytosis

Mesh：

Year:  2018        PMID： 29790152     DOI： 10.1111/bjh.15230

Source DB:  PubMed          Journal:  Br J Haematol        ISSN： 0007-1048            Impact factor:   6.998


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  3 in total

1.  Patient-based prediction algorithm of relapse after allo-HSCT for acute Leukemia and its usefulness in the decision-making process using a machine learning approach.

Authors:  Kyoko Fuse; Shun Uemura; Suguru Tamura; Tatsuya Suwabe; Takayuki Katagiri; Tomoyuki Tanaka; Takashi Ushiki; Yasuhiko Shibasaki; Naoko Sato; Toshio Yano; Takashi Kuroha; Shigeo Hashimoto; Tatsuo Furukawa; Miwako Narita; Hirohito Sone; Masayoshi Masuko
Journal:  Cancer Med       Date:  2019-07-15       Impact factor: 4.452

Review 2.  The Evolution of Single-Cell Analysis and Utility in Drug Development.

Authors:  Shibani Mitra-Kaushik; Anita Mehta-Damani; Jennifer J Stewart; Cherie Green; Virginia Litwin; Christèle Gonneau
Journal:  AAPS J       Date:  2021-08-13       Impact factor: 4.009

Review 3.  How artificial intelligence might disrupt diagnostics in hematology in the near future.

Authors:  Wencke Walter; Claudia Haferlach; Niroshan Nadarajah; Ines Schmidts; Constanze Kühn; Wolfgang Kern; Torsten Haferlach
Journal:  Oncogene       Date:  2021-06-08       Impact factor: 9.867
  3 in total

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