Projects
AIMedTAll
The goal of the AI MedTAll project is to provide medical students with AI competencies. The course content is developed and delivered in collaboration with various medical departments. Students can complete the course flexibly and receive a certificate upon successful completion.
Project Lead: Susanne Eigster
AnNeVer3
The AnNeVer3 project aims to longitudinally integrate the 'neuro' disciplines (neuroanatomy, neurology, and neuroradiology). On the one hand, the project is designed to enhance the understanding of neurological structures and processes; on the other hand, it seeks to reduce 'neurophobia'—the aversion many medical students have toward neuro-related subjects. A core component of the project is the use of an Anatomage Table, which serves as a digital supplement to traditional neuroanatomical dissection and is intended to strengthen fundamental knowledge as a prerequisite for subsequent clinical subjects.
Project Lead: Johanna Rother
DIVINA
DIVINA (Digitale Virtuelle Notaufnahme / Digital Virtual Emergency Department) is a computer-based, simulated virtual emergency department. It is designed for training various medical competencies, particularly clinical reasoning and anamnesis skills. Similar to a real emergency setting, medical students are required to diagnose, treat, and discharge or admit patients to a ward while managing limited resources. The anamnesis system is powered by a large language model that utilizes clearly defined patient cases, thereby creating a realistic and natural communication environment.
Project Lead: Prof. Dr.med. Tobias Raupach, MME
KoMeT
The 'Kommunikationstraining per Medizin-ChatboT' (KoMeT) project establishes a specialized, AI-based communication training program for medical students. It is designed to provide practical, hands-on practice for medical history taking (anamnesis) as well as other challenging and essential clinical communication scenarios. Through an audio interface, students can conduct realistic patient consultations in a flexible and resource-efficient manner. Following these interactions, the AI provides targeted feedback. With these features, the chatbot continuously supports students on their individual learning journeys. As a digital training solution, the program offers students the opportunity to conduct their training sessions independently of location and with ease of access.
Project Lead: Joel Rüttger
M1nd you
The project 'M1nd you' investigates the psychological distress and coping strategies of medical students in the context of the M1 examinations. In a multicenter study, students from various universities are surveyed via anonymous online questionnaires before and after the state examination to analyze stress factors and differences between traditional and integrated/model curricula.
Project Lead: PD Dr. med. Friederike Schröck
TEMMS
TEMMS (Transformation of Emotional and Motivational Factors in Medical Students) is a multicenter, nationwide longitudinal study aiming to investigate the development of medical students throughout their studies and to explore the extent to which this development differs between students in traditional curricula and those in reformed or model curricula.
Project Lead: Johanna Rother
VERO
With VERO (Virtuelle Evaluation und Recherche-Orientierung / Independent and Responsible Online Research), the project partners are developing an AI-based tool to assist in the evaluation of trustworthy online sources. Currently, the project focuses on sources within the field of pediatric cardiology.
Project Lead: Kim Baur
ReAniMed
The interdisciplinary educational project 'ReAniMed – Medicine and Law in Dialogue' brings together medical and law students to collaboratively address complex legal issues in medical practice. Using realistic case studies from areas such as dementia, organ donation, end-of-life decisions, or abortion, students analyze both medical and legal perspectives. The didactic concept combines case-based learning, expert lectures, and a concluding moot court, where the cases are addressed in a simulated court hearing.
Project Lead: PD Dr. Med. Friedrike Schröck
SNAIL
SNAIL (Scale for the assessment of non-experts’ AI literacy) is a questionnaire designed to assess the AI literacy of non-experts. The instrument has been validated in several studies, with its quality criteria—such as reliability, acceptance, and efficiency—systematically examined. The original questionnaire has since been translated into multiple languages and has been utilized in more than 25 published international studies.
Project Lead: Dr. Matthias Carl Laupichler
NeuroNet
The NeuroNet project integrates concepts from functional neuroanatomy, neurosurgery, and functional imaging. The content is delivered through case-based learning, utilizing real patient cases presented as videos and interactive tasks. The course is implemented in both the preclinical and clinical stages of medical education.
Project Lead: Susanne Eigster
AppER
AppER is an application for medical students designed to train clinical reasoning. To this end, students receive new medical cases daily via smartphone notifications. Following the 'key feature' question method, students are prompted to address these cases in accordance with clinical guidelines. In doing so, AppER leverages the well-researched 'testing effect' through state-of-the-art methods. The key innovation of the app lies in its feedback component: students receive automated, personalized feedback tailored to their specific input, generated by a generative AI system. The app is currently in the testing phase.
Project Lead: Prof. Dr. med. Tobias Rauapch
