ReviewJournal of clinical medicine2023
From Vibrations to Visions: Raman Spectroscopy's Impact on Skin Cancer Diagnostics.
Review in Journal of clinical medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 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
12 citing papers in PubMed.
- Raman spectroscopic signatures of prostate cancer progression: correlation with gleason score.Molecular and cellular biochemistry · 2026Article
- Wearable bioelectronics for skin cancer management.Biomaterials · 2026Review
- Precision Diagnosis in Cutaneous Head and Neck Squamous Cell Carcinoma.Biomedicines · 2026Review
- Label-free molecular profiling of cancer using Raman spectroscopy: from fundamentals to clinical applications.Frontiers in oncology · 2026Review
- Detecting metabolic signatures in endometrial cancer: potential applications of Raman spectroscopy.Future oncology (London, England) · 2025Review
- Numerical Analysis of a SiN Digital Fourier Transform Spectrometer for a Non-Invasive Skin Cancer Biosensor.Sensors (Basel, Switzerland) · 2025Article
- A cost-effective approach using generative AI and gamification to enhance biomedical treatment and real-time biosensor monitoring.Scientific reports · 2025Article
- Machine learning-based classification of spatially resolved diffuse reflectance and autofluorescence spectra acquired on human skin for actinic keratoses and skin carcinoma diagnostics aid.Journal of biomedical optics · 2025Article
- Article
- Recent advances in applications of artificial intelligence-assisted Raman spectroscopy in diagnosis of cancers.Frontiers in molecular biosciences · 2025Review
- Multi-Wavelength Raman Differentiation of Malignant Skin Neoplasms.International journal of molecular sciences · 2024Article
- Diagnosis of Skin Cancer: From the Researcher Bench to the Patient's Bedside.Journal of clinical medicine · 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
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Raman spectroscopy, a non-invasive diagnostic technique capturing molecular vibrations, offers significant advancements in skin cancer diagnostics. This review delineates the ascent of Raman spectroscopy from classical methodologies to the forefront of modern technology, emphasizing its precision in differentiating between malignant and benign skin tissues. Our study offers a detailed examination of distinct Raman spectroscopic signatures found in skin cancer, concentrating specifically on squamous cell carcinoma, basal cell carcinoma, and melanoma, across both in vitro and in vivo research. The discussion extends to future possibilities, spotlighting enhancements in portable Raman instruments, the adoption of machine learning for spectral data refinement, and the merging of Raman imaging with other diagnostic techniques. The review culminates by contemplating the broader implications of these advancements, suggesting a trajectory that may significantly optimize the accuracy and efficiency of skin cancer diagnostics.
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Identifiers
What OpenQuestion 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 OpenQuestion graph.