Prostate cancer detection using e-nose and AI for high probability assessment
Abstract This research aims to develop a diagnostic tool that can quickly and accurately detect prostate cancer using electronic nose technology and a neural network trained on a dataset of urine samples from patients diagnosed with both prostate cancer and benign prostatic hyperplasia, which incorp...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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BMC
2023-10-01
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| Series: | BMC Medical Informatics and Decision Making |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12911-023-02312-2 |
| _version_ | 1797452384584073216 |
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| author | J. B. Talens J. Pelegri-Sebastia T. Sogorb J. L. Ruiz |
| author_facet | J. B. Talens J. Pelegri-Sebastia T. Sogorb J. L. Ruiz |
| author_sort | J. B. Talens |
| collection | DOAJ |
| description | Abstract This research aims to develop a diagnostic tool that can quickly and accurately detect prostate cancer using electronic nose technology and a neural network trained on a dataset of urine samples from patients diagnosed with both prostate cancer and benign prostatic hyperplasia, which incorporates a unique data redundancy method. By analyzing signals from these samples, we were able to significantly reduce the number of unnecessary biopsies and improve the classification method, resulting in a recall rate of 91% for detecting prostate cancer. The goal is to make this technology widely available for use in primary care centers, to allow for rapid and non-invasive diagnoses. |
| first_indexed | 2024-03-09T15:07:35Z |
| format | Article |
| id | doaj.art-1ba914ebc3cd4c7abfb4157b79253a58 |
| institution | Directory Open Access Journal |
| issn | 1472-6947 |
| language | English |
| last_indexed | 2024-03-09T15:07:35Z |
| publishDate | 2023-10-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Medical Informatics and Decision Making |
| spelling | doaj.art-1ba914ebc3cd4c7abfb4157b79253a582023-11-26T13:32:25ZengBMCBMC Medical Informatics and Decision Making1472-69472023-10-012311810.1186/s12911-023-02312-2Prostate cancer detection using e-nose and AI for high probability assessmentJ. B. Talens0J. Pelegri-Sebastia1T. Sogorb2J. L. Ruiz3Sensor and Magnetism Group, Institut de Recerca Per a La Gestió Integrada de Zones Costaneres (IGIC), Campus de Gandia, Universitat Politecnica de ValenciaSensor and Magnetism Group, Institut de Recerca Per a La Gestió Integrada de Zones Costaneres (IGIC), Campus de Gandia, Universitat Politecnica de ValenciaSensor and Magnetism Group, Institut de Recerca Per a La Gestió Integrada de Zones Costaneres (IGIC), Campus de Gandia, Universitat Politecnica de ValenciaSurgery Department, Universitat de ValenciaAbstract This research aims to develop a diagnostic tool that can quickly and accurately detect prostate cancer using electronic nose technology and a neural network trained on a dataset of urine samples from patients diagnosed with both prostate cancer and benign prostatic hyperplasia, which incorporates a unique data redundancy method. By analyzing signals from these samples, we were able to significantly reduce the number of unnecessary biopsies and improve the classification method, resulting in a recall rate of 91% for detecting prostate cancer. The goal is to make this technology widely available for use in primary care centers, to allow for rapid and non-invasive diagnoses.https://doi.org/10.1186/s12911-023-02312-2Deep learningNeural networksMachine intelligencee-NoseMOOSY-32Prostate cancer |
| spellingShingle | J. B. Talens J. Pelegri-Sebastia T. Sogorb J. L. Ruiz Prostate cancer detection using e-nose and AI for high probability assessment BMC Medical Informatics and Decision Making Deep learning Neural networks Machine intelligence e-Nose MOOSY-32 Prostate cancer |
| title | Prostate cancer detection using e-nose and AI for high probability assessment |
| title_full | Prostate cancer detection using e-nose and AI for high probability assessment |
| title_fullStr | Prostate cancer detection using e-nose and AI for high probability assessment |
| title_full_unstemmed | Prostate cancer detection using e-nose and AI for high probability assessment |
| title_short | Prostate cancer detection using e-nose and AI for high probability assessment |
| title_sort | prostate cancer detection using e nose and ai for high probability assessment |
| topic | Deep learning Neural networks Machine intelligence e-Nose MOOSY-32 Prostate cancer |
| url | https://doi.org/10.1186/s12911-023-02312-2 |
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