Prediction Model of Amyotrophic Lateral Sclerosis by Deep Learning with Patient Induced Pluripotent Stem Cells.

Journal: Annals of neurology
PMID: 33565152

Abstract

In amyotrophic lateral sclerosis (ALS), early diagnosis is essential for both current and potential treatments. To find a supportive approach for the diagnosis, we constructed an artificial intelligence-based prediction model of ALS using induced pluripotent stem cells (iPSCs). Images of spinal motor neurons derived from healthy control subject and ALS patient iPSCs were analyzed by a convolutional neural network, and the algorithm achieved an area under the curve of 0.97 for classifying healthy control and ALS. This prediction model by deep learning algorithm with iPSC technology could support the diagnosis and may provide proactive treatment of ALS through future prospective research. ANN NEUROL 2021;89:1226-1233.

Authors

  • Keiko Imamura
    Medical-Risk Avoidance Based on iPS Cells Team, RIKEN Center for Advanced Intelligence Project, Kyoto, Japan.
  • Yuichiro Yada
    Center for iPS Cell Research and Application, Kyoto University, Kyoto, Japan.
  • Yuishin Izumi
    Department of Neurology, 3-18-15 Kuramotocho, Tokushima City, 770-8503, Japan.
  • Mitsuya Morita
    Division of Neurology, Department of Internal Medicine, Jichi Medical University, Tochigi, Japan.
  • Akihiro Kawata
    Department of Neurology, Tokyo Metropolitan Neurological Hospital, Tokyo, Japan.
  • Takayo Arisato
    Department of Neurology, National Hospital Organization Minamikyusyu Hospital, Kagoshima, Japan.
  • Ayako Nagahashi
    Medical-Risk Avoidance Based on iPS Cells Team, RIKEN Center for Advanced Intelligence Project, Kyoto, Japan.
  • Takako Enami
    Medical-Risk Avoidance Based on iPS Cells Team, RIKEN Center for Advanced Intelligence Project, Kyoto, Japan.
  • Kayoko Tsukita
    Center for iPS Cell Research and Application, Kyoto University, Kyoto, Japan.
  • Hideshi Kawakami
    Department of Epidemiology, Research Institute for Radiation Biology and Medicine, Hiroshima University, Hiroshima, Japan.
  • Masanori Nakagawa
    Department of Neurology, North Medical Center, Kyoto Prefectural University of Medicine, Kyoto, Japan.
  • Ryosuke Takahashi
    Department of Urology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
  • Haruhisa Inoue
    Medical-Risk Avoidance Based on iPS Cells Team, RIKEN Center for Advanced Intelligence Project, Kyoto, Japan.

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