Not seeing the forest for the trees: combination of path integration and landmark cues in human virtual navigation.

Introduction: In order to successfully move from place to place, our brain often combines sensory inputs from various sources by dynamically weighting spatial cues according to their reliability and relevance for a given task. Two of the most important cues in navigation are the spatial arrangement of landmarks in the environment, and the continuous path integration of travelled distances and changes in direction. Several studies have shown that Bayesian integration of cues provides a good explanation for navigation in environments dominated by small numbers of easily identifiable landmarks.

The Virtual Navigation Toolbox: Providing tools for virtual navigation experiments.

Spatial navigation research in humans increasingly relies on experiments using virtual reality (VR) tools, which allow for the creation of highly flexible, and immersive study environments, that can react to participant interaction in real time. Despite the popularity of VR, tools simplifying the creation and data management of such experiments are rare and often restricted to a specific scope-limiting usability and comparability. To overcome those limitations, we introduce the Virtual Navigation Toolbox (VNT), a collection of interchangeable and independent tools for the development of spatial navigation VR experiments using the popular Unity game engine.

Deep-learning based detection of vessel occlusions on CT-angiography in patients with suspected acute ischemic stroke.

Swift diagnosis and treatment play a decisive role in the clinical outcome of patients with acute ischemic stroke (AIS), and computer-aided diagnosis (CAD) systems can accelerate the underlying diagnostic processes. Here, we developed an artificial neural network (ANN) which allows automated detection of abnormal vessel findings without any a-priori restrictions and in <2 minutes. Pseudo-prospective external validation was performed in consecutive patients with suspected AIS from 4 different hospitals during a 6-month timeframe and demonstrated high sensitivity (≥87%) and negative predictive value (≥93%).

AI-Supported Comprehensive Detection and Quantification of Biomarkers of Subclinical Widespread Diseases at Chest CT for Preventive Medicine.

Automated image analysis plays an increasing role in radiology in detecting and quantifying image features outside of the perception of human eyes. Common AI-based approaches address a single medical problem, although patients often present with multiple interacting, frequently subclinical medical conditions. A holistic imaging diagnostics tool based on artificial intelligence (AI) has the potential of providing an overview of multi-system comorbidities within a single workflow.

Patterns of Safety Incidents in a Neonatal Intensive Care Unit.

Safety incidents preceding manifest adverse events are barely evaluated in neonatal intensive care units (NICUs). This study aimed at identifying frequency and patterns of safety incidents in our NICU. A 6-month prospective clinical study was performed from May to October 2019 in a German 10-bed level III NICU.

Joint Imaging Platform for Federated Clinical Data Analytics.

Purpose: Image analysis is one of the most promising applications of artificial intelligence (AI) in health care, potentially improving prediction, diagnosis, and treatment of diseases. Although scientific advances in this area critically depend on the accessibility of large-volume and high-quality data, sharing data between institutions faces various ethical and legal constraints as well as organizational and technical obstacles.

Methods: The Joint Imaging Platform (JIP) of the German Cancer Consortium (DKTK) addresses these issues by providing federated data analysis technology in a secure and compliant way.

[Results of the hypothermia registry of the University Hospital Dresden from 2010-2017. Application of hypothermia therapy in newborns in Germany].

Introduction: Therapeutic hypothermia (TH) improves the outcome in newborns with hypoxic-ischemic encephalopathy (HIE) and should be used in case of perinatal asphyxia and signs of moderate/severe HIE.

Material/methods: Frequency of HIE and the application of TH were extracted from the neonatal survey, a registry that collects data from all German hospitals, and from the hypothermia registry, established in 2010. The latter was also used to analyze short-term outcomes of the newborns.