Award is to attend the MassBio Digital Health Impact 2019 Symposium with SLAS Scientific Director Mike Tarselli! Congratulations KP.
Interview on TechnologistAssist
Interview by science and technology writer, Marc Landas. "CONVERSATIONS WITH JAMES KIRBY: TRAINING AI FOR INFECTIOUS DISEASE DIAGNOSTICS"
Our Gram stain artificial intelligence platform was selected as a competitor in the 2018 Stat Madness Competition.
Work from our laboratory was selected as a competitor in the 2018 Stat Madness Competition. This bracket style national competition will allow voters to choose among important medical innovations developed at selected medical centers and universities across the United States. Our artificial intelligence-based-platform named Technologist Assist allows automatic imaging and interpretation of Gram stain results and ultimately will provide assisted laboratory diagnostic capabilities at near or remote sites.
Please vote for our work at the Stat Madness website: www.statnews.com/feature/stat-madness/bracket/
Catalyzing Research Innovation
The laboratory has been fortunate to participate in Harvard Catalyst Reactor Program through the "Big Ideas, Small Features” Pilot Grant Award. A description of the program was recently published last week in Harvard Medical School news titled "Catalyzing Research Innovation."
A description of the supported work can be found at: "Reactor Program Awards Eight New Pilot Grants: Supports researchers with novel solutions to major clinical challenges."
Press Release on "Technologist Assist"
New article published online today in Journal of Clinical Microbiology - Artificial intelligence, A New Tool for Interpretation of Bacterial Gram Stains
."Automated Interpretation of Blood Culture Gram Stains using a Deep Convolutional Neural Network" was published online today in the Journal of Clinical Microbiology. Congratulations to co-first authors: postdoctoral fellow, KP Smith, and medical microbiology fellow, Anthony Kang.
The article describes use of artificial intelligence in combination with a Metafer (MetaSystems) automated microscope to automatically interpret blood culture Gram stains without human intervention.
Link to Abstract.
Link to final accepted manuscript file.
Anthony Kang, KP Smith, and I presented posters at the 2017 ASM/ESCMID Conference
on Drug Development to Meet the Challenge of Antimicrobial Resistance, September 6-8, 2017. Posters were on apramycin, inkjet printer-based susceptibility testing methodology, and MAST rapid susceptibility technology, respectively.
Kirby Lab Blog