ArticleNature communications2023
Sample-to-answer platform for the clinical evaluation of COVID-19 using a deep learning-assisted smartphone-based assay.
Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
36 citing papers in PubMed.
- Advances in salivary cortisol monitoring for healthcare applications.RSC advances · 2026Review
- Transport-Reaction-Signal Coupling in Lateral Flow Assays for Next-Generation Point-of-Care Diagnostics.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- DeepBand: A Deep Learning-Enabled Multi-Stage Pipeline for Continuous Automated Quantification of Lateral Flow Assays.Diagnostics (Basel, Switzerland) · 2026Article
- Paper-Based Biosensors for Monitoring Binding, Blocking, and Surrogate Neutralizing Antibody Responses Against Viral Infections.Biosensors · 2026Review
- Interpretable machine learning and signal processing for automated reading and quality control of lateral flow tests for schistosomiasis.Nature communications · 2026Article
- Recent Advances in Microfluidic Chip Technology for Laboratory Medicine: Innovations and Artificial Intelligence Integration.Biosensors · 2026Review
- CRISPR-on-Chip for Point-of-Care Diagnostics.ACS nano · 2026Review
- An intelligent platform for monitoring human serum albumin in urine based on lateral flow immunochromatography.Mikrochimica acta · 2026Article
- From Drops to Decisions: AI/ML-Driven Biofluidics for Clinical Diagnostics and Healthcare Intelligence.Analytical chemistry · 2026Review
- Portable Dual-Mode Biosensor for Quantitative Determination ofBiosensors · 2026Article
- Emerging Trends in Artificial Intelligence-Assisted Colorimetric Biosensors for Pathogen Diagnostics.Sensors (Basel, Switzerland) · 2026Review
- Medical AI across Data Regimes to Promote Proactive Health.Health data science · 2026Review
- A Microfluidic Chip and a Portable Colorimetric Detection Device for the Rapid, Low-Cost, and Accurate Diagnosis of ASFV.Transboundary and emerging diseases · 2026Article
- Smartphone-based video deep learning enables rapid and accurate lateral flow diagnostics.Mikrochimica acta · 2025Article
- Development and Evaluation of a Smartphone App-Based Rapid 25-Hydroxy Vitamin D Test.Diagnostics (Basel, Switzerland) · 2025Article
- Interpretable machine learning and signal processing for automated reading and quality control of lateral flow tests for schistosomiasis.medRxiv : the preprint server for health sciences · 2025Article
- Leveraging Deep Learning to Address Diagnostic Challenges with Insufficient Image Data.ACS sensors · 2025Article
- AI-Powered Embedded System for Rapid Detection of Veterinary Antibiotic Residues in Food-Producing Animals.Antibiotics (Basel, Switzerland) · 2025Article
- POC Sensor Systems and Artificial Intelligence-Where We Are Now and Where We Are Going?Biosensors · 2025Review
- Advancements and Applications of Lateral Flow Assays (LFAs): A Comprehensive Review.Sensors (Basel, Switzerland) · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Since many lateral flow assays (LFA) are tested daily, the improvement in accuracy can greatly impact individual patient care and public health. However, current self-testing for COVID-19 detection suffers from low accuracy, mainly due to the LFA sensitivity and reading ambiguities. Here, we present deep learning-assisted smartphone-based LFA (SMART
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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.