A Combined High-Parameter Flow Cytometry and Machine Learning Approach as a Tool for Classification of MS Patients

被引:0
|
作者
Rebillard, R. [1 ]
Hoornaert, C. J. [2 ]
Grasmuck, C. [1 ]
Tastet, O. [3 ]
Filali, A. [1 ]
Bourbonniere, L. [1 ]
Lahav, B. [1 ]
Poirier, J. [2 ]
Marc, G. [4 ]
Duquette, P. [1 ]
Larochelle, C. [1 ]
Arbour, N. [2 ]
Prat, A. [1 ]
机构
[1] CRCHUM, Neurosci, Montreal, PQ, Canada
[2] CRCHUM, Montreal, PQ, Canada
[3] CHUM, Neuroinflammat, Montreal, PQ, Canada
[4] CHUM, Neurol, Montreal, PQ, Canada
关键词
D O I
暂无
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
P008
引用
收藏
页码:18 / 19
页数:2
相关论文
共 50 条
  • [1] Combinatorial antibody titrations for high-parameter flow cytometry
    Burn, Olivia K.
    Mair, Florian
    Ferrer-Font, Laura
    [J]. CYTOMETRY PART A, 2024, 105 (05) : 388 - 393
  • [2] Identifying multiple sclerosis associated immune profile using a combined high-parameter flow cytometry
    Rebillard, R.
    Chloe, H.
    Grasmuck, C.
    Tastet, O.
    Filali, A.
    Bourbonniere, L.
    Lahav, B.
    Poirier, J.
    Girard, M.
    Duquette, P.
    Larochelle, C.
    Arbour, N.
    Prat, A.
    [J]. MULTIPLE SCLEROSIS JOURNAL, 2022, 28 (1_SUPPL) : 34 - 35
  • [3] Automated antibody dispensing to improve high-parameter flow cytometry throughput and analysis
    Bosteels, Victor
    Van Duyse, Julie
    Ruyssinck, Elien
    Van der Borght, Katrien
    Nguyen, Long
    Gavel, Jannes
    Janssens, Sophie
    Van Isterdael, Gert
    [J]. CYTOMETRY PART A, 2024, 105 (06) : 464 - 473
  • [4] OMIP-097: High-parameter phenotyping of human platelets by spectral flow cytometry
    Spurgeon, Benjamin E. J.
    Frelinger III, Andrew L.
    [J]. CYTOMETRY PART A, 2023, 103 (12) : 935 - 940
  • [5] Setting the gold standard: Commentary on designing and optimizing high-parameter flow cytometry panels
    De Rosa, Stephen C.
    Mahnke, Yolanda D.
    [J]. CYTOMETRY PART A, 2024, 105 (06) : 428 - 429
  • [6] High-parameter flow cytometry by CyTOF empowers comprehensive immune profiling of splenic and pulmonary tissues in aged mice
    Cohen, Michael J.
    Xu, Wenxi
    Li, Stephen
    Bouzekri, Alexandre
    Loh, Christina
    [J]. JOURNAL OF IMMUNOLOGY, 2023, 210 (01):
  • [7] A Clinical Tool for Automated Flow Cytometry Based on Machine Learning Methods
    Takenga, Claude
    Dworzak, Michael
    Diem, Markus
    Berndt, Rolf-Dietrich
    Si, Erling
    Brandstoetter, Michael
    Karawajew, Leonid
    Gau, Melanie
    Kampel, Martin
    [J]. BIOINFORMATICS AND BIOMEDICAL ENGINEERING, IWBBIO 2017, PT II, 2017, 10209 : 537 - 548
  • [8] A Machine Learning Approach to the Classification of Acute Leukemias and Distinction From Nonneoplastic Cytopenias Using Flow Cytometry Data
    Monaghan, Sara A.
    Li, Jeng-Lin
    Liu, Yen-Chun
    Ko, Ming-Ya
    Boyiadzis, Michael
    Chang, Ting-Yu
    Wang, Yu-Fen
    Lee, Chi-Chun
    Swerdlow, Steven H.
    Ko, Bor-Sheng
    [J]. AMERICAN JOURNAL OF CLINICAL PATHOLOGY, 2022, 157 (04) : 546 - 553
  • [9] Studying the cellular basis of small bowel enteropathy using high-parameter flow cytometry in mouse models of primary antibody deficiency
    Mohammed, Ahmed D.
    Ball, Ryan A. W.
    Jolly, Amy
    Nagarkatti, Prakash
    Nagarkatti, Mitzi
    Kubinak, Jason L.
    [J]. FRONTIERS IN IMMUNOLOGY, 2024, 15
  • [10] Review on tool condition classification in milling: A machine learning approach
    Patange, Abhishek D.
    Jegadeeshwaran, R.
    [J]. MATERIALS TODAY-PROCEEDINGS, 2021, 46 : 1106 - 1115