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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Autores principales: Konobu Kimura, Tomohiko Ai, Yuki Horiuchi, Akihiko Matsuzaki, Kumiko Nishibe, Setsuko Marutani, Kaori Saito, Kimiko Kaniyu, Ikki Takehara, Kinya Uchihashi, Akimichi Ohsaka, Yoko Tabe
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
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Medicine
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Science
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Acceso en línea:https://doaj.org/article/e9d17be6387a4566986f527f32e675a1
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https://doaj.org/article/e9d17be6387a4566986f527f32e675a1

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