A geno-clinical decision model for the diagnosis of myelodysplastic syndromes

DOI PDF 参考文献20件 オープンアクセス
  • Nathan Radakovich
    Leukemia Program, Department of Hematology and Medical Oncology, Taussig Cancer Institute, Cleveland Clinic, Cleveland, OH;
  • Manja Meggendorfer
    MLL Munich Leukemia Laboratory, Munich, Bavaria, Germany;
  • Luca Malcovati
    Department of Hematology Oncology, Fondazione IRCCS Policlinico San Matteo, University of Pavia, Pavia, Italy;
  • C. Beau Hilton
    Leukemia Program, Department of Hematology and Medical Oncology, Taussig Cancer Institute, Cleveland Clinic, Cleveland, OH;
  • Mikkael A. Sekeres
    Division of Hematology, Sylvester Comprehensive Cancer Center, University of Miami, Miami, FL;
  • Jacob Shreve
    Department of Internal Medicine, Cleveland Clinic, Cleveland, OH;
  • Yazan Rouphail
    College of Arts and Sciences, The Ohio State University, Columbus, OH;
  • Wencke Walter
    Department of Hematology Oncology, Fondazione IRCCS Policlinico San Matteo, University of Pavia, Pavia, Italy;
  • Stephan Hutter
    Department of Hematology Oncology, Fondazione IRCCS Policlinico San Matteo, University of Pavia, Pavia, Italy;
  • Anna Galli
    Department of Hematology Oncology, Fondazione IRCCS Policlinico San Matteo, University of Pavia, Pavia, Italy;
  • Sara Pozzi
    Department of Hematology Oncology, Fondazione IRCCS Policlinico San Matteo, University of Pavia, Pavia, Italy;
  • Chiara Elena
    Department of Hematology Oncology, Fondazione IRCCS Policlinico San Matteo, University of Pavia, Pavia, Italy;
  • Eric Padron
    Department of Malignant Hematology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL;
  • Michael R. Savona
    Department of Medicine and
  • Aaron T. Gerds
    Leukemia Program, Department of Hematology and Medical Oncology, Taussig Cancer Institute, Cleveland Clinic, Cleveland, OH;
  • Sudipto Mukherjee
    Leukemia Program, Department of Hematology and Medical Oncology, Taussig Cancer Institute, Cleveland Clinic, Cleveland, OH;
  • Yasunobu Nagata
    Department of Translational Hematology and Oncology Research, Taussig Cancer Institute, Cleveland Clinic, Cleveland, OH
  • Rami S. Komrokji
    Department of Malignant Hematology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL;
  • Babal K. Jha
    Department of Translational Hematology and Oncology Research, Taussig Cancer Institute, Cleveland Clinic, Cleveland, OH
  • Claudia Haferlach
    Department of Hematology Oncology, Fondazione IRCCS Policlinico San Matteo, University of Pavia, Pavia, Italy;
  • Jaroslaw P. Maciejewski
    Department of Translational Hematology and Oncology Research, Taussig Cancer Institute, Cleveland Clinic, Cleveland, OH
  • Torsten Haferlach
    MLL Munich Leukemia Laboratory, Munich, Bavaria, Germany;
  • Aziz Nazha
    Leukemia Program, Department of Hematology and Medical Oncology, Taussig Cancer Institute, Cleveland Clinic, Cleveland, OH;

この論文をさがす

説明

<jats:title>Abstract</jats:title> <jats:p>The differential diagnosis of myeloid malignancies is challenging and subject to interobserver variability. We used clinical and next-generation sequencing (NGS) data to develop a machine learning model for the diagnosis of myeloid malignancies independent of bone marrow biopsy data based on a 3-institution, international cohort of patients. The model achieves high performance, with model interpretations indicating that it relies on factors similar to those used by clinicians. In addition, we describe associations between NGS findings and clinically important phenotypes and introduce the use of machine learning algorithms to elucidate clinicogenomic relationships.</jats:p>

収録刊行物

  • Blood Advances

    Blood Advances 5 (21), 4361-4369, 2021-10-29

    American Society of Hematology

参考文献 (20)*注記

もっと見る

関連プロジェクト

もっと見る

詳細情報 詳細情報について

問題の指摘

ページトップへ