ArticleACS sensors2022
Rapid Detection of Urinary Tract Infection in 10 min by Tracking Multiple Phenotypic Features in a 30 s Large-Volume Scattering Video of Urine Microscopy.
Article in ACS sensors, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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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.
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Who cites it
6 citing papers in PubMed, 15 citations in OpenAlex.
- Rapid and accurate preoperative diagnosis of urinary tract infections in urolithiasis patients: clinical validation of the HB&L system.BMC infectious diseases · 2026Article
- Label-Free Optical Imaging of Nanoscale Single Entities.ACS sensors · 2024Review
- Deep Learning-Based Culture-Free Bacteria Detection in Urine Using Large-Volume Microscopy.Biosensors · 2024Article
- Simple Imaging System for Label-Free Identification of Bacterial Pathogens in Resource-Limited Settings.International journal of biomedical imaging · 2024Article
- Optical Methods for Label-Free Detection of Bacteria.Biosensors · 2022Review
- Label-free single-particle imaging approach for ultra-rapid detection of pathogenic bacteria in clinical samples.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
Corrections and comments
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Authors and funding
11 authors at 3 institutions in 2 countries.
Funding
Abstract
Rapid point-of-care (POC) diagnosis of bacterial infection diseases provides clinical benefits of prompt initiation of antimicrobial therapy and reduction of the overuse/misuse of unnecessary antibiotics for nonbacterial infections. We present here a POC compatible method for rapid bacterial infection detection in 10 min. We use a large-volume solution scattering imaging (LVSi) system with low magnifications (1-2×) to visualize bacteria in clinical samples, thus eliminating the need for culture-based isolation and enrichment. We tracked multiple intrinsic phenotypic features of individual cells in a short video. By clustering these features with a simple machine learning algorithm, we can differentiate
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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 Socratic graph.