Prostate cancer detection using e-nose and AI for high probability assessment.

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.

Low Complexity System on Chip Design to Acquire Signals from MOS Gas Sensor Applications.

Analog signals from gas sensors are used to recognize all types of VOC (Volatile Organic Compound) substances, such as toxic gases, tobacco or ethanol. The processes to recognize these substances include acquisition, treatment and machine learning for classification, which can all be efficiently implemented on a Field Programmable Gate Array (FPGA) aided by Low-Voltage Differential Signaling (LVDS). This article proposes a low-cost 11-bit effective number of bits (ENOB) sigma-delta Analog to Digital Converter (ADC), with an SNR of 75.

Development of the MOOSY4 eNose IoT for Sulphur-Based VOC Water Pollution Detection.

In this paper, we describe a new low-cost and portable electronic nose instrument, the Multisensory Odor Olfactory System MOOSY4. This prototype is based on only four metal oxide semiconductor (MOS) gas sensors suitable for IoT technology. The system architecture consists of four stages: data acquisition, data storage, data processing, and user interfacing.

Body satisfaction and sexual health in Dutch female university students.

Studies in the field of body image have primarily addressed its negative aspects, such as body dissatisfaction. The present study focused instead on women who are satisfied with their bodies and on how body satisfaction relates to sexual health. A sample of 319 Dutch female university students completed an online survey that included items about body image evaluation, body image investment, overweight preoccupation, body image affect during sexual activity, sexual frequency, sexual functioning, and sexual self-esteem.