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Artificial intelligence deep learning model assessment of leukocyte counts and proliferation in endometrium from women with and without polycystic ovary syndrome.
Kangasniemi, Marika H; Komsi, Elina K; Rossi, Henna-Riikka; Liakka, Annikki; Khatun, Masuma; Chen, Joseph C; Paulson, Mariana; Hirschberg, Angelica L; Arffman, Riikka K; Piltonen, Terhi T.
Afiliação
  • Kangasniemi MH; Department of Obstetrics and Gynecology, PEDEGO Research Unit, Medical Research Center, Oulu University Hospital, University of Oulu, Oulu, Finland.
  • Komsi EK; Department of Obstetrics and Gynecology, PEDEGO Research Unit, Medical Research Center, Oulu University Hospital, University of Oulu, Oulu, Finland.
  • Rossi HR; Department of Obstetrics and Gynecology, PEDEGO Research Unit, Medical Research Center, Oulu University Hospital, University of Oulu, Oulu, Finland.
  • Liakka A; Department of Pathology, Medical Research Center, Oulu University Hospital, University of Oulu, Oulu, Finland.
  • Khatun M; Department of Obstetrics and Gynecology, PEDEGO Research Unit, Medical Research Center, Oulu University Hospital, University of Oulu, Oulu, Finland.
  • Chen JC; Department of Obstetrics, Gynecology and Reproductive Sciences, University of California, San Francisco, California.
  • Paulson M; Department of Women's and Children's Health, Karolinska Institutet, Stockholm, Sweden; Department of Gynecology and Reproductive Medicine, Karolinska University Hospital, Stockholm, Sweden.
  • Hirschberg AL; Department of Women's and Children's Health, Karolinska Institutet, Stockholm, Sweden; Department of Gynecology and Reproductive Medicine, Karolinska University Hospital, Stockholm, Sweden.
  • Arffman RK; Department of Obstetrics and Gynecology, PEDEGO Research Unit, Medical Research Center, Oulu University Hospital, University of Oulu, Oulu, Finland.
  • Piltonen TT; Department of Obstetrics and Gynecology, PEDEGO Research Unit, Medical Research Center, Oulu University Hospital, University of Oulu, Oulu, Finland. Electronic address: terhi.piltonen@oulu.fi.
F S Sci ; 3(2): 174-186, 2022 05.
Article em En | MEDLINE | ID: mdl-35560015
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Síndrome do Ovário Policístico / Aprendizado Profundo / Anovulação Idioma: En Ano de publicação: 2022 Tipo de documento: Article
Texto completo
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XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Síndrome do Ovário Policístico / Aprendizado Profundo / Anovulação Idioma: En Ano de publicação: 2022 Tipo de documento: Article