ArticleEuropean archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery2017
Feasibility of electronic nose technology for discriminating between head and neck, bladder, and colon carcinomas.
Article in European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 3 of them syntheses that pooled it.
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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
30 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Diagnostic performance of volatile organic compounds analysis and electronic noses for detecting colorectal cancer: a systematic review and meta-analysis.Frontiers in oncology · 2024Pooled it
- Breath analysis for the detection of digestive tract malignancies: systematic review.BJS open · 2021Pooled it
- Pooled it
- Exhaled breath analysis with the use of an electronic nose to predict response to immune checkpoint inhibitors in patients with metastatic melanoma: melaNose trial.Frontiers in immunology · 2025Trial
- Machine learning-enabled diagnosis of viral respiratory infections from exhaled volatile organic compound analysis.BMC pulmonary medicine · 2026Article
- Diagnostic performance of eNose technology in detecting colorectal cancer recurrence: A prospective evaluation.PloS one · 2026Article
- A standardized lexicon of body odor words crafted from 17 countries.Scientific data · 2025Article
- Article
- Is an Electronic Nose Able to Predict Clinical Response following Neoadjuvant Treatment of Rectal Cancer? A Prospective Pilot Study.Journal of clinical medicine · 2024Article
- Application of electronic nose technology in the diagnosis of gastrointestinal diseases: a review.Journal of cancer research and clinical oncology · 2024Review
- Electronic Noses: From Gas-Sensitive Components and Practical Applications to Data Processing.Sensors (Basel, Switzerland) · 2024Review
- Diagnosis of chondrosarcoma in a noninvasive way using volatile organic compounds in exhaled breath: a pilot study.Future oncology (London, England) · 2024Article
- Advancing Colorectal Cancer Diagnosis with AI-Powered Breathomics: Navigating Challenges and Future Directions.Diagnostics (Basel, Switzerland) · 2023Review
- Diagnosis of Carcinogenic Pathologies through Breath Biomarkers: Present and Future Trends.Biomedicines · 2023Review
- The Detection of Colorectal Cancer through Machine Learning-Based Breath Sensor Analysis.Diagnostics (Basel, Switzerland) · 2023Article
- Article
- The Role of a Polymer-Based E-Nose in the Detection of Head and Neck Cancer from Exhaled Breath.Sensors (Basel, Switzerland) · 2022Article
- Breath Analysis: A Promising Tool for Disease Diagnosis-The Role of Sensors.Sensors (Basel, Switzerland) · 2022Review
- Review
- Cancer Diagnosis by Neural Network Analysis of Data from Semiconductor Sensors.Diagnostics (Basel, Switzerland) · 2020Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Electronic nose (e-nose) technology has the potential to detect cancer at an early stage and can differentiate between cancer origins. Our objective was to compare patients who had head and neck squamous cell carcinoma (HNSCC) with patients who had colon or bladder cancer to determine the distinctive diagnostic characteristics of the e-nose. Feasibility study An e-nose device was used to collect samples of exhaled breath from patients who had HNSCC and those who had bladder or colon cancer, after which the samples were analyzed and compared. One hundred patients with HNSCC, 40 patients with bladder cancer, and 28 patients with colon cancer exhaled through an e-nose for 5 min. An artificial neural network was used for the analysis, and double cross-validation to validate the model. In differentiating HNSCC from colon cancer, a diagnostic accuracy of 81 % was found. When comparing HNSCC with bladder cancer, the diagnostic accuracy was 84 %. A diagnostic accuracy of 84 % was found between bladder cancer and colon cancer. The e-nose technique using double cross-validation is able to discriminate between HNSCC and colon cancer and between HNSCC and bladder cancer. Furthermore, the e-nose technique can distinguish colon cancer from bladder cancer.
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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.