An explainable self-attention deep neural network for detecting mild cognitive impairment using multi-input digital drawing tasks.

Background: Mild cognitive impairment (MCI) is an early stage of cognitive decline which could develop into dementia. An early detection of MCI is a crucial step for timely prevention and intervention. Recent studies have developed deep learning models to detect MCI and dementia using a bedside task like the classic clock drawing test (CDT).

Alprazolam and lorazepam overdose and the absence of brainstem reflexes.

Benzodiazepines (BZDs) rarely cause respiratory depression and death. On the other hand, high-dose BZDs may lead to profound sedation and diminished brainstem functions that mimic other structural brain lesions as described in our case: a 70-year-old unresponsive woman. She was hypothermic and had rapid shallow breathing.