Evidence map›Paper›PMID 42451596›Full record

ReviewMolecules (Basel, Switzerland)2026

Emerging Plasmonic Nanomaterials for SERS-Based Disease Diagnostics: Innovations, Clinical Challenges, and AI Integration.

Rabeea Razaq, Arslan Younas, Muhammad Azam Qamar, Ahmad Farhan, Aman Khalid, Amna Akhtar, Muntaha Anwar, Tania Shad, Zulfiqar Ahmad Rehan, Syed Imran Hassan

Abstract readReview
In one paragraph

Review in Molecules (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

10 authors.

Rabeea RazaqDepartment of Chemistry, University of Agriculture Faisalabad, Faisalabad 38000, Pakistan.
Arslan YounasDepartment of Chemistry, University of Agriculture Faisalabad, Faisalabad 38000, Pakistan.
Muhammad Azam QamarDepartment of Chemistry, School of Science, University of Management and Technology, Lahore 54770, Pakistan.ORCID 0000-0002-7645-7133
Ahmad FarhanDepartment of Chemistry, University of Agriculture Faisalabad, Faisalabad 38000, Pakistan.ORCID 0009-0006-6129-2192
Aman KhalidSchool of Mechanical, Medical and Process Engineering, Faculty of Engineering, Queensland University of Technology, Brisbane, QLD 4000, Australia.
Amna AkhtarDepartment of Energy Systems Engineering, University of Agriculture Faisalabad, Faisalabad 38000, Pakistan.
Muntaha AnwarDepartment of Chemistry, University of Agriculture Faisalabad, Faisalabad 38000, Pakistan.
Tania ShadDepartment of Zoology, Wildlife and Fisheries, University of Agriculture Faisalabad, Faisalabad 38000, Pakistan.
Zulfiqar Ahmad RehanDepartment of Chemistry, College of Science, Sultan Qaboos University, Al Khod, Muscat 123, Oman.ORCID 0000-0001-8508-3156
Syed Imran HassanDepartment of Chemistry, College of Science, Sultan Qaboos University, Al Khod, Muscat 123, Oman.ORCID 0000-0003-1839-184X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Surface-enhanced Raman spectroscopy (SERS) has emerged as a transformative tool in biomedical diagnostics, offering a highly sensitive and non-invasive method for detecting molecular biomarkers at exceptionally low concentrations. This approach takes advantage of the plasmonic characteristics of customized metallic nanostructures that produce intense localized electromagnetic fields via localized surface plasmon resonance and facilitate electron transfer reactions that notoriously enhance the intrinsically weak Raman scattering signals of molecular entities which reside on or next to their surfaces. SERS-based assays have shown remarkable potential in detecting cancer biomarkers, circulating tumor DNA (ctDNA), and proteins at early stages, enabling timely and targeted intervention. Additionally, the combination of SERS with AI-driven data analysis has facilitated real-time diagnostics, enhancing the precision and efficiency of point-of-care testing. Despite its promising capabilities, challenges such as substrate fouling, signal degradation, and the need for better biocompatibility remain. Nevertheless, ongoing research in substrate development, coupled with advances in AI, positions SERS as a leading technology for future diagnostic tools. This paper explores the current state of SERS in biomedical applications, highlighting its potential to revolutionize diagnostics and personalized medicine while addressing the existing limitations and future research directions.

Indexed as

Artificial IntelligenceNanostructuresSpectrum Analysis, RamanBiomarkers, TumorHumansPrecision MedicineSurface Plasmon ResonanceBiomarkers, Tumorartificial intelligencebiomedical diagnosticsearly disease detectionpersonalized medicinesurface-enhanced raman spectroscopy

Identifiers

PMID42451596
PMCPMC13363543

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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.