Evidence map›Paper›PMID 41973240›Full record

ArticleBiomedical microdevices2026

A comparative study of COVID-19 point-of-care detection across human biofluids using MEMS-based near-infrared spectroscopy and machine learning.

Ahmed Abdelkhalik, Mazen Erfan, Bassem Mortada, Mohamed Gaber, Moataz Bellah Abdelaleem, Hala Hafez, Samia A Girgis, Ossama Mansour, Bassam Saadany, Yasser M Sabry and 1 more

Abstract readComparative Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Biomedical microdevices, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Ahmed AbdelkhalikSi-Ware Systems, 3 Khaled Ibn Al-Waleed Street, Heliopolis, Cairo, Egypt.
Mazen ErfanSi-Ware Systems, 3 Khaled Ibn Al-Waleed Street, Heliopolis, Cairo, Egypt. mazen.erfan@eng.asu.edu.eg.
Bassem MortadaSi-Ware Systems, 3 Khaled Ibn Al-Waleed Street, Heliopolis, Cairo, Egypt.
Mohamed GaberSi-Ware Systems, 3 Khaled Ibn Al-Waleed Street, Heliopolis, Cairo, Egypt.
Moataz Bellah AbdelaleemFaculty of Medicine, Clinical Pathology Department, Ain Shams University, Cairo, Egypt.
Hala HafezFaculty of Medicine, Clinical Pathology Department, Ain Shams University, Cairo, Egypt.
Samia A GirgisFaculty of Medicine, Clinical Pathology Department, Ain Shams University, Cairo, Egypt.
Ossama MansourFaculty of Medicine, Ear, Nose and Throat Department, Ain Shams University, Cairo, Egypt.
Bassam SaadanySi-Ware Systems, 3 Khaled Ibn Al-Waleed Street, Heliopolis, Cairo, Egypt.
Yasser M SabrySi-Ware Systems, 3 Khaled Ibn Al-Waleed Street, Heliopolis, Cairo, Egypt. yasser.sabry@eng.asu.edu.eg.
Diaa KhalilSi-Ware Systems, 3 Khaled Ibn Al-Waleed Street, Heliopolis, Cairo, Egypt.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study explores the use of near-infrared (NIR) spectroscopy in the 1.3–2.6 μm wavelength range, employing a handheld miniaturized microelectromechanical systems (MEMS)-based spectrometer for the rapid, non-invasive detection of COVID-19 from various biofluids. A total of 238 samples—including nasopharyngeal (NSP) swabs, nasal swabs, and saliva—from both COVID-19 positive and negative individuals are analysed. Machine learning algorithms process the spectral data to develop predictive models for the disease classification. Models based on a single biofluid achieve detection accuracies between 75% and 80%, while combining scans from multiple biofluids of the same individual improves accuracy to 88%. The study highlights trade-offs between sample accessibility and diagnostic performance. Overall, the findings demonstrate that NIR spectroscopy serves as a viable low-cost, portable, and rapid point-of-care (POC) solution, with strong potential for scalable mass screening—particularly in resource-limited settings.

Indexed as

Body FluidsCOVID-19Machine LearningMicro-Electrical-Mechanical SystemsPoint-of-Care SystemsHumansSARS-CoV-2Spectroscopy, Near-InfraredATRCOVID-19Human biofluidsInfectious diseaseMEMS FTIR spectrometerNIR spectroscopyPCR

Identifiers

PMID41973240
PMCPMC13076386

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Registered trials

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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.