Automated diagnostic support system with deep learning algorithms for distinction of Philadelphia chromosome-negative myeloproliferative neoplasms using peripheral blood specimen

Automated diagnostic support system with deep learning algorithms for distinction of Philadelphia chromosome-negative myeloproliferative neoplasms using peripheral blood specimen

Abstract Philadelphia chromosome-negative myeloproliferative neoplasms (Ph-negative MPNs) such as polycythemia vera (PV), essential thrombocythemia (ET), and primary myelofibrosis are characterized by abnormal proliferation of mature bone marrow cell lineages. Since various non-hematologic disorders...

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Bibliographic Details
Main Authors: Konobu Kimura, Tomohiko Ai, Yuki Horiuchi, Akihiko Matsuzaki, Kumiko Nishibe, Setsuko Marutani, Kaori Saito, Kimiko Kaniyu, Ikki Takehara, Kinya Uchihashi, Akimichi Ohsaka, Yoko Tabe
Format: Article
Language:English
Published: Nature Portfolio 2021-02-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-021-82826-9

Internet

https://doi.org/10.1038/s41598-021-82826-9

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