 This paper reviews the current state of research into the neurophysiological determinants of occupational stress and burnout. It discusses the use of EEG analysis, diagnostic pet imaging, cortisol, prolactin, adrenal corticotropic hormone, ACTH, corticotropin-releasing hormone, CRH, and thyroid hormones, as well as plasma BDNF levels, to identify markers for these conditions. Additionally, it explores the potential of artificial intelligence, AI, based big data analysis to provide more accurate diagnoses. The authors conclude that the combination of traditional kinometric tests, neurophysiological tests and AI-based big data analysis can provide new classifiers with high accuracy and new diagnostic methods. This article was authored by Darius Mikolayevsky, Gelantem Asiak, and Emilia Mikolajewska.