ReviewNanoscale advances2023
Machine learning-augmented surface-enhanced spectroscopy toward next-generation molecular diagnostics.
Review in Nanoscale advances, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 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
39 citing papers in PubMed.
- Research progress of AI assisted nano-SERS technology in rapid identification of multi species oral pathogenic biofilms.Mikrochimica acta · 2026Review
- Surface-Enhanced Raman Spectroscopy for Viral Diagnostics: Principles, Strategies, Clinical Challenges, and Future Directions.Chemical reviews · 2026Review
- Strategies for Multiplexing Plasmonic Biosensing.Sensors (Basel, Switzerland) · 2026Review
- Surface Chemistry-Driven Surface-Enhanced Raman Scattering Fingerprinting of Aptamers on Silver Colloids.ACS applied optical materials · 2026Article
- A Review of SERS-Based Bacterial Detection from Nanomaterials to Integrated Clinical Platforms.Biosensors · 2026Review
- Machine Learning-Enabled Intelligent Analysis of Surface-Enhanced Raman Scattering: Methods, Applications, and Perspectives.Molecules (Basel, Switzerland) · 2026Review
- Identification of geographical origins of Ophiocordyceps sinensis (Berk.) via machine learning-assisted surface-enhanced Raman spectroscopy.Analytical and bioanalytical chemistry · 2026Article
- Overview in Machine-Learning-Assisted Sensing Techniques for Monitoring COVID-19.Micromachines · 2026Review
- Immunochromatographic SERS sensor-deep learning combined strategy for intelligent diagnosis of chronic kidney disease.Mikrochimica acta · 2026Article
- AI-Guided SERS Defines a Pan-Cancer Diagnostic Biomarker.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Emerging frontiers in SERS-integrated optical waveguides: advancing portable and ultra-sensitive detection for trace liquid analysis.Light, science & applications · 2025Review
- AI‑driven photonic noses: from conventional sensors to cloud‑to-edge intelligent microsystems.Microsystems & nanoengineering · 2025Review
- Advances in the Application of Surface-Enhanced Raman Spectroscopy for Quality Control of Cereal Foods.Foods (Basel, Switzerland) · 2025Review
- Determining mosquito age using surface-enhanced Raman spectroscopy and artificial neural networks: insights into the influence of origin and sex.Parasites & vectors · 2025Article
- Advances in MEMS, Optical MEMS, and Nanophotonics Technologies for Volatile Organic Compound Detection and Applications.Small science · 2025Review
- Nanomaterial-Based Molecular Imaging in Cancer: Advances in Simulation and AI Integration.Biomolecules · 2025Review
- Emerging trends in SERS-based veterinary drug detection: multifunctional substrates and intelligent data approaches.NPJ science of food · 2025Review
- The Evolving Landscape of Cervical Cancer: Breakthroughs in Screening and Therapy Through Integrating Biotechnology and Artificial Intelligence.Molecular biotechnology · 2025Review
- Integration of Nanoengineering with Artificial Intelligence and Machine Learning in Surface-Enhanced Raman Spectroscopy (SERS) for the Development of Advanced Biosensing Platforms.Advanced sensor research · 2025Article
- Artificial Intelligence and Machine Learning Algorithms-Powered SERS Techniques for Early Theragnosis of Oral Squamous Cell Carcinoma.Journal of maxillofacial and oral surgery · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The world today is witnessing the significant role and huge demand for molecular detection and screening in healthcare and medical diagnosis, especially during the outbreak of COVID-19. Surface-enhanced spectroscopy techniques, including Surface-Enhanced Raman Scattering (SERS) and Infrared Absorption (SEIRA), provide lattice and molecular vibrational fingerprint information which is directly linked to the molecular constituents, chemical bonds, and configuration. These properties make them an unambiguous, nondestructive, and label-free toolkit for molecular diagnostics and screening. However, new issues in molecular diagnostics, such as increasing molecular species, faster spread of viruses, and higher requirements for detection accuracy and sensitivity, have brought great challenges to detection technology. Advancements in artificial intelligence and machine learning (ML) techniques show promising potential in empowering SERS and SEIRA with rapid analysis and automatic data processing to jointly tackle the challenge. This review introduces the combination of ML and SERS/SEIRA by investigating how ML algorithms can be beneficial to SERS/SEIRA, discussing the general process of combining ML and SEIRA/SERS, highlighting the molecular diagnostics and screening applications based on ML-combined SEIRA/SERS, and providing perspectives on the future development of ML-integrated SEIRA/SERS. In general, this review offers comprehensive knowledge about the recent advances and the future outlook regarding ML-integrated SEIRA/SERS for molecular diagnostics and screening.
Identifiers
What Socratic holds
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.