Digital patient twins for personalized therapeutics and pharmaceutical manufacturing.

Digital twins are virtual models of physical artefacts that may or may not be synchronously connected, and that can be used to simulate their behavior. They are widely used in several domains such as manufacturing and automotive to enable achieving specific quality goals. In the health domain, so-called digital patient twins have been understood as virtual models of patients generated from population data and/or patient data, including, for example, real-time feedback from wearables.

Methods Used in the Development of Common Data Models for Health Data: Scoping Review.

Background: Common data models (CDMs) are essential tools for data harmonization, which can lead to significant improvements in the health domain. CDMs unite data from disparate sources and ease collaborations across institutions, resulting in the generation of large standardized data repositories across different entities. An overview of existing CDMs and methods used to develop these data sets may assist in the development process of future models for the health domain, such as for decision support systems.

Development of a Proxy-Free Objective Assessment Tool of Instrumental Activities of Daily Living in Mild Cognitive Impairment Using Smart Home Technologies.

Background: The assessment of activities of daily living (ADL) is essential for dementia diagnostics. Even in mild cognitive impairment (MCI), subtle deficits in instrumental ADL (IADL) may occur and signal a higher risk of conversion to dementia. Thus, sensitive and reliable ADL assessment tools are important.

Pediatric trauma care with computed tomography--criteria for CT scanning.

Trauma centers, trauma management concepts, as well as integration of whole-body computed tomography (CT) reduced mortality significantly. The accuracy of a trauma care algorithm with emergency CT in children was evaluated. Data of 71 children with emergency CT were recorded retrospectively.