ArticleiScience2022
Drift compensation on electronic nose data for non-invasive diagnosis of prostate cancer by urine analysis.
Article in iScience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it, 27 citations in OpenAlex.
- eNose technologies in the detection of cancer: a systematic review and meta-analysis.The oncologist · 2026Pooled it
- Accuracy of a new electronic nose for prostate cancer diagnosis in urine samples.International journal of urology : official journal of the Japanese Urological Association · 2022Trial
- Olfactory Science and Technology in Prostate Cancer Diagnosis: From Invertebrate Models to Artificial Intelligence.Life (Basel, Switzerland) · 2026Review
- Overcoming the Limits of Cross-Sensitivity: Pattern Recognition Methods for Chemiresistive Gas Sensor Array.Nano-micro letters · 2024Review
- Prostate cancer risk stratification via eNose urine odor analysis: a preliminary report.Frontiers in oncology · 2024Article
- Determination of Odor Air Quality Index (Molecules (Basel, Switzerland) · 2022Article
- An Experimental Apparatus for E-Nose Breath Analysis in Respiratory Failure Patients.Diagnostics (Basel, Switzerland) · 2022Article
- Article
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Diagnostic protocol for prostate cancer (KP) is affected by poor accuracy and high false-positive rate. The most promising innovative approach is based on urine analysis by electronic noses (ENs), highlighting a specific correlation between urine alteration and KP presence. Although EN could be exploited to develop non-invasive KP diagnostic tools, no study has already introduced EN into clinical practice, most probably because of drift issues that hinder EN scaling up from research objects to large-scale diagnostic devices. This study, proposing an EN for non-invasive KP detection, describes the data processing protocol applied to a urine headspace dataset acquired over 9 months, comprising 81 patients with KP and 41 controls, for compensating the drift. It proved effective in mitigating drift on 1-year-old sensors by restoring accuracy from 55% up to 80%, achieved by new sensors not subjected to drift. The model achieved, on double-blind validation, a balanced accuracy of 76.2% (CI
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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.