A Pipeline for Real-Time Synchronization of Relevant Data in Pediatric Emergencies.

Pediatric emergencies are rare events that require precise medical intervention. The dosing of medication is particularly tricky. The challenges require technical aids for automatic dosage calculation without restricting the emergency physicians' ability to act.

[OPTINOFA-Intelligent assistance service for structured assessment in the emergency department].

Background: Case numbers in central emergency departments (EDs) have risen during the past decade in Germany, leading to recurrent overcrowding, increased risks in emergency care, and elevated costs. Particularly the fraction of outpatient emergency treatments has increased disproportionately. Within the framework of the Optimization of emergency care by structured triage with intelligent assistant service (OPTINOFA, Förderkennzeichen [FKZ] 01NVF17035) project, an intelligent assistance service was developed.

Development of a Clinical Decision Support System for Smart Algorithms in Emergency Medicine.

The development of clinical decision support systems (CDSS) is complex and requires user-centered planning of assistive interventions. Especially in the setting of emergency care requiring time-critical decisions and interventions, it is important to adapt a CDSS to the needs of the user in terms of acceptance, usability and utility. In the so-called ENSURE project, a user-centered approach was applied to develop the CDSS intervention.

Mobile Robotic Telepresence Between Hospital and School: Lessons Learned.

If a pupil falls seriously ill, it is not only a shock for the pupil himself or herself, but also for his or her family and classmates. The project "Virtual Classroom" of the Heilbronn University in cooperation with the foundation "Big Help for Little Heroes" therefore tries to maintain the daily school routine and thus the contact with friends as far as possible with the help of mobile telepresence robots in the classroom from home or from the hospital. Here there are both technical and human factors that contribute to success or failure.

Evaluation of Chatbot Prototypes for Taking the Virtual Patient's History.

In medical education Virtual Patients (VP) are often applied to train students in different scenarios such as recording the patient's medical history or deciding a treatment option. Usually, such interactions are predefined by software logic and databases following strict rules. At this point, Natural Language Processing/Machine Learning (NLP/ML) algorithms could help to increase the overall flexibility, since most of the rules can derive directly from training data.