ReviewRSC advances2018
Skin cancer detection using non-invasive techniques.
Review in RSC advances, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers, 2 of them syntheses that pooled 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.
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
43 citing papers in PubMed, 2 syntheses or guidelines pooled it, 159 citations in OpenAlex.
- Artificial intelligence for skin cancer detection and classification for clinical environment: a systematic review.Frontiers in medicine · 2023Pooled it
- Comparative Analysis of Diagnostic Techniques for Melanoma Detection: A Systematic Review of Diagnostic Test Accuracy Studies and Meta-Analysis.Frontiers in medicine · 2021Pooled it
- MSF-VMDNet for multi class segmentation of skin cancer whole slide images using a multi frequency dual encoder network.Scientific reports · 2026Article
- Active Versus Passive Infrared Thermography for Skin Cancer Detection: A Diagnostic Accuracy Study.Cancers · 2026Article
- Highlighting a histopathological dilemma: atypical dermatofibrosarcoma protuberans diagnosed with multimodal dermoscopy.Skin health and disease · 2026Article
- Review
- Estimation of Scattering Properties Modifications Caused by In Vivo Human Skin Optical Clearing Using Line-Field Confocal Optical Coherence Tomography.Journal of biophotonics · 2025Article
- Artificial Intelligence-Based Wearable Sensing Technologies for the Management of Cancer, Diabetes, and COVID-19.Biosensors · 2025Review
- Non-invasive characterization of melanoma depth at single-cell resolution.Journal of the European Academy of Dermatology and Venereology : JEADV · 2025Article
- Impact of Scattering Variation Measured by Line-Field Confocal Optical Coherence Tomography on Fluorescence Measurement by Optical Spectroscopy: A Study on Phantoms and Human Skin Models.Skin pharmacology and physiology · 2025Article
- TRP channels and cancer modulation: a voyage beyond metabolic reprogramming, oxidative stress and the advent of nanotechnologies in targeted therapy.Journal of experimental & clinical cancer research : CR · 2025Review
- Review of Non-Invasive Imaging Technologies for Cutaneous Melanoma.Biosensors · 2025Review
- Automatic melanoma and non-melanoma skin cancer diagnosis using advanced adaptive fine-tuned convolution neural networks.Discover oncology · 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
- Skin cancer detection using dermoscopic images with convolutional neural network.Scientific reports · 2025Article
- Near-infrared spectroscopy-enabled electromechanical systems for fast mapping of biomechanics and subcutaneous diagnosis.Science advances · 2024Article
- Skin Cancer Image Classification Using Artificial Intelligence Strategies: A Systematic Review.Journal of imaging · 2024Review
- Diagnosing skin cancer using social spider optimization (SSO) and error correcting output codes (ECOC) with weighted hamming distance.Scientific reports · 2024Article
- Feasibility Study on the Use of Infrared Cameras for Skin Cancer Detection under a Proposed Data Degradation Model.Sensors (Basel, Switzerland) · 2024Article
- A novel skin cancer detection model using modified finch deep CNN classifier model.Scientific reports · 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
8 authors at 3 institutions in 5 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Skin cancer is the most common form of cancer and is globally rising. Historically, the diagnosis of skin cancers has depended on various conventional techniques which are of an invasive manner. A variety of commercial diagnostic tools and auxiliary techniques are available to detect skin cancer. This article explains in detail the principles and approaches involved for non-invasive skin cancer diagnostic methods such as photography, dermoscopy, sonography, confocal microscopy, Raman spectroscopy, fluorescence spectroscopy, terahertz spectroscopy, optical coherence tomography, the multispectral imaging technique, thermography, electrical bio-impedance, tape stripping and computer-aided analysis. The characteristics of an ideal screening test are outlined, and the authors pose several points for clinicians and scientists to consider in the evaluation of current and future studies of skin cancer detection and diagnosis. This comprehensive review critically analyses the literature associated with the field and summarises the recent updates along with their merits and demerits.
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.