[Machine learning methods in differential diagnosis of ACTH-dependent hypercortisolism].

Aim: To develop a noninvasive method of differential diagnosis of ACTH-dependent hypercortisolism, as well as to evaluate the effectiveness of an optimal algorithm for predicting the probability of ectopic ACTH syndrome (EAS) obtained using machine learning methods based on the analysis of clinical data.

Materials And Methods: As part of a single-center, one-stage, cohort study, a retrospective prediction of the probability of EAS among patients with ACTH-dependent hypercortisolism was carried out. Patients were randomly stratified into 2 samples: training (80%) and test (20%).

Morphogenesis of asymmetry of rat brain nuclei under normal conditions and during exposure to microgravitation.

Histological and morphometrical analysis of the brain and peripheral analyzers revealed proliferative migration abnormalities of brain development and neuron differentiation in mammals during a space flight, which can limit space exploration.