ArticleJournal of fungi (Basel, Switzerland)2023
Digital Platform for Automatic Qualitative and Quantitative Reading of a Cryptococcal Antigen Point-of-Care Assay Leveraging Smartphones and Artificial Intelligence.
Article in Journal of fungi (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed, 20 citations in OpenAlex.
- AI-Enhanced Point-of-Care Diagnostics for Infectious Diseases in Resource-Limited Settings: A Scoping Review.Tropical medicine & international health : TM & IH · 2026Article
- Review
- Diagnostic performance of a biotin-labeled 4D1 sandwich ELISA for serum antigen detection in talaromycosis.PLoS neglected tropical diseases · 2026Article
- Accuracy and Acceptability of the VISITECT CD4 Advanced Disease Test Compared With the PIMA CD4 Test at the Point of Care as Part of the Advanced HIV Disease Care Package: A Mixed-Methods Study.Open forum infectious diseases · 2026Article
- Smartphone-Powered Automated Image Recognition Tool for Multianalyte Rapid Tests: Application to Infectious Diseases.Analytical chemistry · 2025Article
- New Ground in Antifungal Discovery and Therapy for Invasive Fungal Infections: Innovations, Challenges, and Future Directions.Journal of fungi (Basel, Switzerland) · 2024Review
- Rapid CD4 cell count determination andIJID regions · 2024Article
- Artificial intelligence-driven mobile interpretation of a semi-quantitative cryptococcal antigen lateral flow assay.IMA fungus · 2024Article
- Measuring the performance of computer vision artificial intelligence to interpret images of HIV self-testing results.Frontiers in public health · 2024Article
- Rapid Point-of-Care Identification of Aspergillus Species in Microbial Keratitis.JAMA ophthalmology · 2023Article
- The Use of Machine Learning for Image Analysis Artificial Intelligence in Clinical Microbiology.Journal of clinical microbiology · 2023Review
Corrections and comments
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Authors and funding
8 authors at 1 institution in 2 countries.
Funding
Abstract
Cryptococcosis is a fungal infection that causes serious illness, particularly in immunocompromised individuals such as people living with HIV. Point of care tests (POCT) can help identify and diagnose patients with several advantages including rapid results and ease of use. The cryptococcal antigen (CrAg) lateral flow assay (LFA) has demonstrated excellent performance in diagnosing cryptococcosis, and it is particularly useful in resource-limited settings where laboratory-based tests may not be readily available. The use of artificial intelligence (AI) for the interpretation of rapid diagnostic tests can improve the accuracy and speed of test results, as well as reduce the cost and workload of healthcare professionals, reducing subjectivity associated with its interpretation. In this work, we analyze a smartphone-based digital system assisted by AI to automatically interpret CrAg LFA as well as to estimate the antigen concentration in the strip. The system showed excellent performance for predicting LFA qualitative interpretation with an area under the receiver operating characteristic curve of 0.997. On the other hand, its potential to predict antigen concentration based solely on a photograph of the LFA has also been demonstrated, finding a strong correlation between band intensity and antigen concentration, with a Pearson correlation coefficient of 0.953. The system, which is connected to a cloud web platform, allows for case identification, quality control, and real-time monitoring.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.