University of Colorado and Fluid Imaging Technologies to Research Use of Artificial Intelligence for Identification of Bloodborne Bacteria

Study Aims to Automatically Determine Bacterial Species for Fast, Lifesaving Treatment

Scarborough, ME: Sepsis due to staph, strep, listeria, E. coli and other bacterial infections may soon be detected much earlier thanks to new machine learning and NanoFlow Imaging® technologies. Global laboratory instrumentation manufacturer Fluid Imaging Technologies, Scarborough, ME (www.fluidimaging.com), and the University of Colorado Boulder have entered into an exclusive agreement to conduct primary laboratory research aimed at determining whether the University’s proprietary artificial intelligence software can detect bloodborne bacteria and identify the species from images collected using the manufacturer’s patented FlowCam® Nano particle imaging and analysis system. In the study, entitled “Application of Convolutional Neural Networks and Flow Imaging Microscopy to Analysis of Blood Infections”, researchers are to evaluate the 10 strains of bacteria most responsible for the 1.5 million sepsis cases and 250,000 fatalities annually in the United States per CDC data. These cases cost upwards of $6 billion in annual Medicare payments, according to the Centers for Medicare and Medicaid Services. The top 10 most wanted bacterial strains are:

  • Staphylococcus areus
  • Staphylococcus epidermis
  • Staphylococcus haemolyticus
  • Enterococcus faecalis
  • Streptococcus agalactiae
  • Escherichia coli
  • Streptococcus pneumonia
  • Listeria monoctytogenes
  • Enterobacter cloacae
  • Enterobacter aerogenase

To be conducted under the direction and supervision of the University’s principal investigator, Dr. Theodore Randolph, for the Department of Chemical and Biological Engineering, the research study is to establish training set data for the 10 strains from representative Nano-Flow Imaging® microscopy images then apply the University’s deep convolutional neural network software to train a computer to identify the microorganisms automatically. Ultimately, the research team hopes to reduce the time required to correctly identify the bacterial species causing an infection from several days in a laboratory to 60 minutes or less on-site via the FlowCam Nano. Once identified, the proper antibiotic may be prescribed for fast, effective treatment.

Featuring pioneering, patented optical technology for unprecedented image resolution, the FlowCam Nano is the world’s first flow imaging particle analyzer that automatically detects, images and characterizes micron- and sub-micron size particles and microorganisms ranging in size from 300 nm to 10+ µm. In addition to imaging bacterial strains, the imaging particle analyzer has proven effective in imaging red and white blood cells, protein agglomerates, silicon oil droplets, carbon nanotubes, yeast, and a variety of other nanoparticles.

For more information, contact Fluid Imaging Technologies, Inc.; 200 Enterprise Drive, Scarborough, Maine 04074; 207.289.3200.; Fax 207.289.3101; www.fluidimaging.com

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