Alzheimer's Disease stage identification using deep learning models.

Objective: The aim of this research is to identify the stage of Alzheimer's Disease (AD) patients through the use of mobility data and deep learning models. This process facilitates the monitoring of the disease and allows actions to be taken in order to provide the optimal treatment and the prevention of complications.

Materials And Methods: We employed data from 35 patients with AD collected by smartphones for a week in a daycare center.

Surveillance for angiosarcoma of the liver among vinyl chloride workers.

Objective: We report the results of our angiosarcoma of the liver (ASL) registry to assess the occurrence, the impact of exposures to vinyl chloride, and to quantify latency.

Methods: We examined more than 73,000 death certificates of North American workers employed between 1940 and 2008.

Results: We found 13 deaths of ASL among workers with vinyl chloride exposure.