ArticleScientific reports2021
Rapid diagnosis of COVID-19 using FT-IR ATR spectroscopy and machine learning.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 24 papers.
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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
24 citing papers in PubMed, 63 citations in OpenAlex.
- Predicting the Risk of Proteinuria Based on Blood Plasma Fourier-Transform Infrared Spectroscopy and Machine Learning Algorithms From Pregnant Women and Newborns.Analytical science advances · 2026Article
- A comparative study of COVID-19 point-of-care detection across human biofluids using MEMS-based near-infrared spectroscopy and machine learning.Biomedical microdevices · 2026Article
- Review
- Rapid reagent free COVID19 detection using MEMS based FTIR spectroscopy and machine learning in NIR and MIR regions.Scientific reports · 2025Article
- Safe-by-Design Strategies for Intranasal Drug Delivery Systems: Machine and Deep Learning Solutions to Differentiate Epithelial Tissues via Attenuated Total Reflection Fourier Transform Infrared Spectroscopy.ACS pharmacology & translational science · 2025Article
- Infrared Spectroscopy Coupled with Machine Learning Algorithms to Investigate Vascular Dysfunction in Ovariectomy: An Animal Model Study.ACS omega · 2025Article
- Efficient and accurate determination of the degree of substitution of cellulose acetate using ATR-FTIR spectroscopy and machine learning.Scientific reports · 2025Article
- Surface-Enhanced Raman Scattering Combined with Machine Learning for Rapid and Sensitive Detection of Anti-SARS-CoV-2 IgG.Biosensors · 2024Article
- Infrared spectroscopy as a new approach for early fabry disease screening: a pilot study.Orphanet journal of rare diseases · 2024Article
- Two-trace two-dimensional correlation spectra (2T2D-COS) analysis using FTIR spectra to monitor the immune response by COVID-19.Journal of molecular medicine (Berlin, Germany) · 2024Article
- Editorial: Technological innovations for improved prevention and diagnosis of oral disease.Frontiers in oral health · 2024Article
- Surface-Enhanced Raman Analysis of Uric Acid and Hypoxanthine Analysis in Fractionated Bodily Fluids.Nanomaterials (Basel, Switzerland) · 2023Article
- Article
- Current trends in COVID-19 diagnosis and its new variants in physiological fluids: Surface antigens, antibodies, nucleic acids, and RNA sequencing.Trends in analytical chemistry : TRAC · 2022Review
- Diagnostic performance of attenuated total reflection Fourier-transform infrared spectroscopy for detecting COVID-19 from routine nasopharyngeal swab samples.Scientific reports · 2022Article
- Insights into Biochemical Sources and Diffuse Reflectance Spectral Features for Colorectal Cancer Detection and Localization.Cancers · 2022Article
- Spectroscopic methods for COVID-19 detection and early diagnosis.Virology journal · 2022Review
- Article
- Review
- Development of novel spectroscopic and machine learning methods for the measurement of periodic changes in COVID-19 antibody level.Measurement : journal of the International Measurement Confederation · 2022Article
Corrections and comments
- Erratum issued
Authors and funding
12 authors at 5 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Early diagnosis of COVID-19 in suspected patients is essential for contagion control and damage reduction strategies. We investigated the applicability of attenuated total reflection (ATR) Fourier transform infrared (FTIR) spectroscopy associated with machine learning in oropharyngeal swab suspension fluid to predict COVID-19 positive samples. The study included samples of 243 patients from two Brazilian States. Samples were transported by using different viral transport mediums (liquid 1 or 2). Clinical COVID-19 diagnosis was performed by the RT-PCR. We built a classification model based on partial least squares (PLS) associated with cosine k-nearest neighbours (KNN). Our analysis led to 84% and 87% sensitivity, 66% and 64% specificity, and 76.9% and 78.4% accuracy for samples of liquids 1 and 2, respectively. Based on this proof-of-concept study, we believe this method could offer a simple, label-free, cost-effective solution for high-throughput screening of suspect patients for COVID-19 in health care centres and emergency departments.
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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.