Sensor and Magnetism Group, Institut de Recerca Per a La Gestió Integrada de Zones Costaneres (IGIC), Campus de Gandia, Universitat Politecnica de Valencia, Paranimf 1, Grao de Gandia, 46000, Valencia, Spain.
Educacion, Conselleria de Educacion, Cultura y Deporte, Av. de Campanar, 32, 46015, Valencia, Spain.
BMC Med Inform Decis Mak. 2023 Oct 6;23(1):205. doi: 10.1186/s12911-023-02312-2.
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.
本研究旨在开发一种诊断工具，该工具使用电子鼻技术和基于前列腺癌和良性前列腺增生患者尿液样本数据集训练的神经网络，结合独特的数据冗余方法，快速、准确地检测前列腺癌。通过分析这些样本的信号，我们能够显著减少不必要的活检数量并改进分类方法，使前列腺癌检测的召回率达到 91%。目标是使这项技术在初级保健中心广泛使用，以实现快速、无创诊断。
