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Enhanced Rabies Surveillance Using a Direct Rapid Immunohistochemical Test

Enhanced Rabies Surveillance Using a Direct Rapid Immunohistochemical Test

Published on: April 30, 2019

AI-enhanced rapid diagnostic testing platform for mass opisthorchiasis screening.

Prem Junsawang¹, Anchalee Techasen^2,3, Kannika Wiratchawa¹

¹Visual Intelligence Laboratory, Department of Statistics, Faculty of Science, Khon Kaen University, Khon Kaen, Thailand.

Scientific Reports

|August 23, 2025

Summary

A new AI-powered platform standardizes Opisthorchis viverrini (OV) rapid diagnostic test (RDT) interpretation for mass screening. This technology improves early detection of liver fluke infections, crucial for preventing cholangiocarcinoma in Southeast Asia.

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Area of Science:

Medical Diagnostics
Artificial Intelligence in Public Health
Parasitology

Background:

Cholangiocarcinoma (CCA) is a significant health concern in the Mekong Basin, strongly associated with Opisthorchis viverrini (OV) infection.
Early detection of OV infection is vital for at-risk populations in endemic areas.
Current OV rapid diagnostic tests (RDTs) rely on subjective visual interpretation, leading to variability and data digitization challenges.

Purpose of the Study:

To introduce the OV-RDT platform, a cloud-based AI system for standardized interpretation of OV-RDT results.
To facilitate efficient mass screening for opisthorchiasis.
To enhance early detection and public health interventions in OV-endemic regions.

Main Methods:

Development of a cross-platform (Android/iOS) cloud-based system with a mobile app, intelligent dashboard, and AI/data processing servers.
Implementation of AI models (EfficientNet-B5) for image quality assessment and T-band grading of OV-RDT images.
Extensive field validation in northeastern Thailand, processing over 100,000 samples.

Main Results:

The AI platform demonstrated high accuracy: 98% for image quality assessment and 95% for OV infection grading.
The system processed over 100,000 samples effectively during field testing in a high-prevalence region.
Healthcare workers reported high satisfaction (4.41/5.00) with the user-friendly interface and dashboard capabilities.

Conclusions:

The OV-RDT platform offers a standardized, AI-driven solution for mass screening of opisthorchiasis.
The technology shows significant promise for improving early detection and public health strategies in Southeast Asia.
Further external validation is recommended to confirm generalizability across diverse geographical areas.