ArticleACS sensors2024
3D Superclusters with Hybrid Bioinks for Early Detection in Breast Cancer.
Article in ACS sensors, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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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.
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Who cites it
10 citing papers in PubMed.
- Surface-Enhanced Raman Spectroscopy in Breast Cancer Detection: A Bibliometric Review and Landscape of Global Trends.Biosensors · 2026Review
- Review
- Gold- or Silver-Nanoparticle SERS Platforms for Plasma-Based Diagnostics and AI-Driven Analysis.Sensors (Basel, Switzerland) · 2026Review
- Raman Spectroscopy in Cancer Diagnostics and Surgery: 25 Years of Progress from Surface-Enhanced Raman Spectroscopy to Artificial Intelligence─A Bibliometric and Visualized Study.Analytical chemistry · 2026Review
- Label-free saliva screening platform using M13 bacteriophage-based 3D plasmonic structures for MRONJ diagnosis.Scientific reports · 2026Article
- Acoustic Bioprinting: A Glimpse Into an Emerging Field.Small methods · 2026Review
- Research progress of surface-enhanced Raman scattering technology in tumor liquid biopsy.Frontiers in molecular biosciences · 2026Review
- Fabrication of serum-based SERS-tailored 3D structures for thyroid cancer diagnosis.Scientific reports · 2025Article
- Surface-enhanced Raman spectroscopy for label-free cancer liquid biopsy: from fundamentals to clinical analysis of biofluid.Frontiers in chemistry · 2025Review
- Integrated SERS-Microfluidic Sensor Based on Nano-Micro Hierarchical Cactus-like Array Substrates for the Early Diagnosis of Prostate Cancer.Biosensors · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The surface-enhanced Raman scattering (SERS) technique has garnered significant interest due to its ultrahigh sensitivity, making it suitable for addressing the growing demand for disease diagnosis. In addition to its sensitivity and uniformity, an ideal SERS platform should possess characteristics such as simplicity in manufacturing and low analyte consumption, enabling practical applications in complex diagnoses including cancer. Furthermore, the integration of machine learning algorithms with SERS can enhance the practical usability of sensing devices by effectively classifying the subtle vibrational fingerprints produced by molecules such as those found in human blood. In this study, we demonstrate an approach for early detection of breast cancer using a bottom-up strategy to construct a flexible and simple three-dimensional (3D) plasmonic cluster SERS platform integrated with a deep learning algorithm. With these advantages of the 3D plasmonic cluster, we demonstrate that the 3D plasmonic cluster (3D-PC) exhibits a significantly enhanced Raman intensity through detection limit down to 10
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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.