By Stephen Bishop, MBA, MS, CLS, MLS(ASCP)CM, CPHQ
This article explores the evolution of respiratory pathogen diagnostics and the transformative role of artificial intelligence (AI) in the clinical laboratory. From early microscopy and culture techniques to PCR advancements during the Influenza A (H1N1) and COVID-19 pandemics, diagnostic methods have steadily advanced in speed and accuracy. The article examines the benefits and limitations of antigen and molecular testing before introducing AI subsets—including machine learning, deep learning, and natural language processing—and their applications in assay optimization, result interpretation, and clinical decision support. Emphasis is placed on improving turnaround times, diagnostic stewardship, and proactive patient care through AI integration.
LEARNING OBJECTIVES
Upon completion of this article, the reader will be able to:
- Discuss the utility for the advancement of respiratory pathogen diagnosis.
- Discuss timelines of respiratory illnesses and the development of laboratory testing with each.
- Define the limitations of antigen testing in the identification of respiratory pathogens.
- Describe the different subsets of AI and each of their purposes in the use of respiratory pathogens identification.

Stephen Bishop, MBA, MS, CLS, MLS(ASCP)CM, CPHQ is currently the Market Director of Laboratory Services at CommonSpirit Health, Southern California. Stephen is passionate about healthcare leadership, clinical laboratory education, and process improvement.

