Machine learning enabled classification of lung cancer cell lines co-cultured with fibroblasts with lightweight convolutional neural network for initial diagnosis.

Journal: Journal of biomedical science
PMID: 39180048

Abstract

BACKGROUND: Identification of lung cancer subtypes is critical for successful treatment in patients, especially those in advanced stages. Many advanced and personal treatments require knowledge of specific mutations, as well as up- and down-regulations of genes, for effective targeting of the cancer cells. While many studies focus on individual cell structures and delve deeper into gene sequencing, the present study proposes a machine learning method for lung cancer classification based on low-magnification cancer outgrowth patterns in a 2D co-culture environment.

Authors

  • Adam Germain
    Department of Bioengineering, University of Texas at Arlington, 500 UTA Blvd ERB244, Arlington, TX, 76010, USA.
  • Alex Sabol
    Department of Computer Science, University of Texas at Arlington, Arlington, TX, USA.
  • Anjani Chavali
    Department of Bioengineering, University of Texas at Arlington, 500 UTA Blvd ERB244, Arlington, TX, 76010, USA.
  • Giles Fitzwilliams
    Department of Bioengineering, University of Texas at Arlington, 500 UTA Blvd ERB244, Arlington, TX, 76010, USA.
  • Alexa Cooper
    Department of Biology, University of Texas at Arlington, Arlington, TX, USA.
  • Sandra Khuon
    Department of Nursing, University of Texas at Arlington, Arlington, TX, USA.
  • Bailey Green
    Department of Bioengineering, University of Texas at Arlington, 500 UTA Blvd ERB244, Arlington, TX, 76010, USA.
  • Calvin Kong
    Department of Bioengineering, University of Texas at Arlington, 500 UTA Blvd ERB244, Arlington, TX, 76010, USA.
  • John Minna
    Hamon Center for Therapeutic Oncology Research, Department of Internal Medicine and Department of Pharmacology, University of Texas Southwestern Medical Center, Dallas, TX; Harold C. Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TX.
  • Young-Tae Kim
    Department of Bioengineering, University of Texas at Arlington, Arlington, TX 76019, USA; Department of Urology, University of Texas Southwestern Medical Center at Dallas, Dallas, TX 75235, USA.

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