ArticleDiagnostics (Basel, Switzerland)2022
Open-Source, Adaptable, All-in-One Smartphone-Based System for Quantitative Analysis of Point-of-Care Diagnostics.
Article in Diagnostics (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- DeepBand: A Deep Learning-Enabled Multi-Stage Pipeline for Continuous Automated Quantification of Lateral Flow Assays.Diagnostics (Basel, Switzerland) · 2026Article
- The evolution of next-generation lateral flow assays for bacterial and fungal diagnostics.Mikrochimica acta · 2026Review
- Portable Raspberry Pi Platform for Automated Interpretation of Lateral Flow Strip Tests.Sensors (Basel, Switzerland) · 2026Article
- Rapid screening for acute rheumatic fever using machine learning analysis of host tissue reactive antibodies.Scientific reports · 2025Article
- Emerging Trends in Point-of-Care Technology Development for Oncology in Low- and Middle-Income Countries.JCO global oncology · 2025Review
- Development and evaluation of a rapid skin taurine measurement device using skin blotting for the early detection of dehydration.Japan journal of nursing science : JJNS · 2025Article
- Enhancing lateral flow immunoassay performance for cardiac troponin I detection with pore-size tailored silica nanoparticles and smartphone-based "AdaptiScan" analysis.Frontiers in bioengineering and biotechnology · 2025Article
- Does Prehospital Suspicion of Sepsis Shorten Time to Administration of Antibiotics in the Emergency Department? A Retrospective Study in One University Hospital.Journal of clinical medicine · 2023Article
- Comparative assessment of the SjSAP4-incorporated gold immunochromatographic assay for the diagnosis of human schistosomiasis japonica.Frontiers in public health · 2023Article
- Visual Detection of COVID-19 from Materials Aspect.Advanced fiber materials · 2022Review
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Point-of-care (POC) diagnostics, in particular lateral flow assays (LFA), represent a great opportunity for rapid, precise, low-cost and accessible diagnosis of disease. Especially with the ongoing coronavirus disease 2019 (COVID-19) pandemic, rapid point-of-care tests are becoming everyday tools for identification and prevention. Using smartphones as biosensors can enhance POC devices as portable, low-cost platforms for healthcare and medicine, food and environmental monitoring, improving diagnosis and documentation in remote, low-resource locations. We present an open-source, all-in-one smartphone-based system for quantitative analysis of LFAs. It consists of a 3D-printed photo box, a smartphone for image acquisition, and an R Shiny software package with modular, customizable analysis workflow for image editing, analysis, data extraction, calibration and quantification of the assays. This system is less expensive than commonly used hardware and software, so it could prove very beneficial for diagnostic testing in the context of pandemics, as well as in low-resource countries.
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