(untitled) (The Conference Hub, 2025)
Modern industrial processes are characterized by high intensity and technological complexity, which are accompanied by workers’ exposure to a wide range of harmful and hazardous occupational factors. These include physical (noise, vibration, adverse microclimate, dust exposure, ionizing and non-ionizing radiation), chemical, biological, as well as psycho-physiological stressors. Traditional hygienic assessment methods are often retrospective in nature and do not always ensure timely identification of emerging health risks. Since such approaches are largely based on regulatory threshold values and statistical analyses, their capacity for early detection of unfavorable health changes remains limited. Therefore, the integration of artificial intelligence (AI) technologies capable of processing large heterogeneous datasets and generating predictive risk models is becoming increasingly relevant for forecasting potential adverse effects of workplace hazards on workers’ health.