Improved detection of small pulmonary embolism on unenhanced computed tomography using an artificial intelligence-based algorithm - a single centre retrospective study.

To preliminarily verify the feasibility of a deep-learning (DL) artificial intelligence (AI) model to localize pulmonary embolism (PE) on unenhanced chest-CT by comparison with pulmonary artery (PA) CT angiography (CTA). In a monocentric study, we retrospectively reviewed 99 oncological patients (median age in years: 64 (range: 28-92 years); percentage of female: 39.4%) who received unenhanced and contrast-enhanced chest CT examinations in one session between January 2020 and October 2022 and who were diagnosed incidentally with PE.

Electrophysiological responses to digit stimulation in a tactile oddball paradigm.

Sensory memory traces are assessed via oddball paradigms in which deviant (infrequent) stimuli are interspersed into a string of standard (frequent) stimuli. Once a memory trace for the standard is established, the deviant spurs a change detection response measured via the resulting event related potential (ERP). Response magnitude is sensitive to the differences in stimuli properties or categories and influenced by individual experience.