Published on in Vol 8, No 4 (2020): April

A Hematologist-Level Deep Learning Algorithm (BMSNet) for Assessing the Morphologies of Single Nuclear Balls in Bone Marrow Smears: Algorithm Development

A Hematologist-Level Deep Learning Algorithm (BMSNet) for Assessing the Morphologies of Single Nuclear Balls in Bone Marrow Smears: Algorithm Development

A Hematologist-Level Deep Learning Algorithm (BMSNet) for Assessing the Morphologies of Single Nuclear Balls in Bone Marrow Smears: Algorithm Development

Journals

  1. Sirinukunwattana K, Aberdeen A, Theissen H, Sousos N, Psaila B, Mead A, Turner G, Rees G, Rittscher J, Royston D. Artificial intelligence–based morphological fingerprinting of megakaryocytes: a new tool for assessing disease in MPN patients. Blood Advances 2020;4(14):3284 View
  2. Jiang X, Zeng Y, Xiao S, He S, Ye C, Qi Y, Zhao J, Wei D, Hu M, Chen F. Automatic Detection of Coronary Metallic Stent Struts Based on YOLOv3 and R-FCN. Computational and Mathematical Methods in Medicine 2020;2020:1 View
  3. Mori J, Kaji S, Kawai H, Kida S, Tsubokura M, Fukatsu M, Harada K, Noji H, Ikezoe T, Maeda T, Matsuda A. Assessment of dysplasia in bone marrow smear with convolutional neural network. Scientific Reports 2020;10(1) View
  4. Smith M, Westerling-Bui T, Wilcox A, Schwartz J. Screening For Bone Marrow Cellularity Changes in Cynomolgus Macaques in Toxicology Safety Studies Using Artificial Intelligence Models. Toxicologic Pathology 2021;49(4):905 View
  5. Walter W, Haferlach C, Nadarajah N, Schmidts I, Kühn C, Kern W, Haferlach T. How artificial intelligence might disrupt diagnostics in hematology in the near future. Oncogene 2021;40(25):4271 View