Abstract
This work consists of a study to detect prostate cancer using E-senses devices based on electronic tongue and electronic nose systems. Therefore, two groups of confirmed prostate cancer and control patients were invited to participate through urine and exhaled breath samples, where the control patients group was categorized as Benign Prostatic Hyperplasia, Prostatitis, and Healthy patients. Afterward, the samples were subsequently classified using Pattern Recognition and machine learning methods, where the results were compared through clinical history, obtaining a 92.9% success rate in the PCa and control samples’ classification accuracy by using eTongue and a 100% success rate of classification using eNose.
| Original language | English |
|---|---|
| Article number | 11 |
| Journal | Chemosensors |
| Volume | 12 |
| Issue number | 1 |
| DOIs | |
| State | Published - Jan 2024 |
Bibliographical note
Publisher Copyright:© 2024 by the authors.
ASJC Scopus Subject Areas
- Analytical Chemistry
- Physical and Theoretical Chemistry
Keywords
- electronic nose
- electronic tongue
- exhaled breath
- machine learning
- pattern recognition
- prostate cancer
- urine
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