Peer-reviewed study found 98% concordance between Techcyte’s digital workflow and brightfield microscopy in routine clinical laboratory testing.
A peer-reviewed study published in Diagnostics demonstrates that Techcyte’s AI-assisted digital parasitology workflow achieved excellent agreement with traditional brightfield microscopy in routine clinical laboratory conditions.
The prospective study, conducted by the Institute for Infectious Diseases at the University of Bern, evaluated 208 consecutive diagnostic stool samples over three months using Techcyte’s Human Fecal Wet Mount (HFW) algorithm. Results showed approximately 98% overall concordance with traditional microscopy and a Cohen’s kappa of 0.915, indicating strong alignment between the AI-assisted digital review and conventional methods.
“Our goal was to evaluate how an AI-assisted digital parasitology workflow performs under everyday laboratory conditions,” says Dr Alexander Oberli, lead author of the study, in a release. “We observed excellent agreement with light microscopy and consistent performance across repeated testing. The ability to pre-classify objects of interest helped streamline review while maintaining appropriate expert oversight.”
Workflow Detected Missed Findings
Beyond the prospective testing, researchers evaluated a reference panel of archived samples and conducted precision studies involving repeated scans and testing across multiple days. These analyses demonstrated consistent detection and reproducibility, supporting the stability of the workflow under routine laboratory conditions.
The study documented cases where the AI-assisted workflow flagged low-burden parasitic findings that were initially missed during manual microscopy review and subsequently confirmed upon re-examination. The authors positioned the workflow as a screening and efficiency tool that supports laboratory professionals by prioritizing areas of interest for expert analysis.
“This publication reflects the kind of clinically grounded evidence laboratories look for when evaluating digital pathology solutions,” says Brian Cahoon, director of clinical pathology at Techcyte, in a release. “It demonstrates how AI can be responsibly integrated into existing workflows to improve consistency and efficiency while keeping diagnostic decision-making firmly in the hands of trained professionals.”
Addressing Laboratory Challenges
The findings highlight the potential of AI-assisted digital parasitology to support laboratories facing increasing workload, staffing pressures, and variability inherent to manual microscopy. By demonstrating strong agreement with established diagnostic methods and consistent performance under routine conditions, the study reinforces the role of digital platforms as practical solutions for modernizing microscopy-based workflows.
The research provides peer-reviewed evidence for how AI can be deployed to enhance efficiency, consistency, and confidence in diagnostic practice as laboratories continue adopting digital pathology solutions.
Photo credit: Techcyte
