New Perspectives on the Automated Microbiology Lab: Realizing the Potential of Artificial Intelligence

How to Gain Efficiency without Compromising Results

With requests for “on-demand” testing, pressure from clinicians for rapid turnaround times, and the significant and growing shortage of skilled technologists, microbiology laboratories are increasingly being asked to do more with less. As a result, juggling various clinical, operations, and financial imperatives is a never-ending task for laboratory managers and scientists at the bench.

The ability to drive efficiencies without compromising quality is a significant concern in this delicate balancing act. Using artificial intelligence (AI) and machine learning (ML) to identify and prioritize clinically relevant specimens is key to streamlining workflows to let staff concentrate their skills on what matters most.

This webinar will review the potential that AI and ML offers the clinical microbiology laboratory, outline currently available solutions that leverage these advances, and present an overview of clinical experience with an in vitro diagnostic device that incorporates ML algorithms with digital image capture. 

Learning Objectives

This webinar will help you:

• Clarify the difference and relationship between artificial intelligence and machine learning
• Review barriers to adoption of these technologies in the microbiology lab
• Review recent applications of AI and ML in the microbiology lab
• Assess the implications of removing negative cultures from a workflow

Watch on Demand       Download Slides (PDF, 329KB)

For research use only. Not for diagnostic procedures.

This webinar is produced by Whitehat Communications, a provider of continuing education programs in clinical laboratory sciences that has been approved by the ASCLS P.A.C.E.™ Program. One P.A.C.E. credit hour will be provided for this complimentary, basic-level program.

Steven Giglio, PhD,Scientific Director, LBT Innovations

Dr. Giglio has more than 25 years of experience in public health microbiology and a history of developing and implementing new, rapid diagnostic technologies. Giglio is responsible for setting the scientific strategy and direction for LBT product development activities. Previously, he led several large infectious disease laboratories across South Australia.

Rhys Hill, Research Director, LBT Innovations

After receiving a bachelor’s degrees in mathematics and computer science from the University of Adelaide, Hill became a researcher at the Australian Centre for Visual Technologies, which has since become the Australian Institute of Machine Learning. He was the leader of the initial research and development for the core Automated Plate Assessment System (APAS™) technology for both the imaging hardware and the AI and image processing software.

Chris Ramsey, PhD, Business Development Director, Clever Culture Systems

Dr. Ramsey earned a doctorate in human genetics from the University of California, Los Angeles, followed by a post-doctorate fellowship in immunology at The Scripps Research Institute. For the past 14 years, he has worked with several reputable clinical diagnostic companies, contributing to their sales and marketing departments. In his current role, Ramsey manages the commercialization of the Clever Culture Systems APAS™ Independence instrument in the U.S.