Artificial intelligence-driven mobile interpretation of a semi-quantitative cryptococcal antigen lateral flow assay.

ABSTRACT:

Objectives

Cryptococcosis remains a severe global health concern, underscoring the urgent need for rapid and reliable diagnostic solutions. Point-of-care tests (POCTs), such as the cryptococcal antigen semi-quantitative (CrAgSQ) lateral flow assay (LFA), offer promise in addressing this challenge. However, their subjective interpretation poses a limitation. Our objectives encompass the development and validation of a digital platform based on Artificial Intelligence (AI), assessing its semi-quantitative LFA interpretation performance, and exploring its potential to quantify CrAg concentrations directly from LFA images.

Methods

We tested 53 cryptococcal antigen (CrAg) concentrations spanning from 0 to 5000 ng/ml. A total of 318 CrAgSQ LFAs were inoculated and systematically p

SUBMITTER: Bermejo-Pelaez D 

PROVIDER: S-EPMC11365246 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature