Medicine 1 provides the fundamental medical knowledge necessary for processing and interpreting medical information. The course focuses on cytology and genetics, as well as the anatomy, physiology, diagnosis, prevention, and treatment of the cardiovascular system, the respiratory system, and the musculoskeletal system. The course also covers the fundamentals of medical decision-making and evidence-based medicine. The goal is to understand medical concepts and to interpret information from clinical settings in a professional manner.
Programming 1 introduces the fundamental concepts and ways of thinking in software development. Students learn about variables, data types, control structures, arrays, and basic algorithms, and apply them in practical exercises. Another focus is on object-oriented programming, covering concepts such as classes, objects, inheritance, and polymorphism. The goal is to design, implement, and test simple programs in a structured manner, as well as to systematically develop algorithmic solutions.
The Introductory Project helps students get started in their studies in Medical Informatics. Working in small teams, students tackle a manageable task related to computer science and put their initial conceptual ideas into practice. At the same time, the course teaches the fundamentals of independent study and scientific work. Workshops on research, time management, presentation skills, communication, and exam preparation help students develop effective learning and work strategies.
Medical data must be structured, documented, and searchable. This module therefore covers the fundamentals of medical documentation, terminology, and classification, as well as information retrieval. Topics covered include thesauri, semantic indexing, and search methods, as well as classification systems such as ICD, OPS, DRG, MeSH, TNM, and MedDRA. The goal is to systematically organize medical information and apply appropriate computational methods for documentation and research.
This module covers fundamental concepts in computer science and lays the groundwork for further technical and programming-related coursework. Topics covered include binary number representation, coding, Boolean algebra, processors, computer architectures, and operating systems. Students learn how information is represented and processed in computer systems and develop a fundamental understanding of the interaction between hardware and software.
Linear Algebra provides the mathematical foundations required in many areas of medical informatics. The course focuses on vectors, matrices, systems of linear equations, linear transformations, eigenvalues and eigenvectors, as well as real and complex numbers. Students learn to understand mathematical structures, formally describe practical problems, and apply appropriate methods to solve them. At the same time, the course fosters logical thinking and the ability to solve problems abstractly.
Medicine 2 expands on the fundamentals of medicine to include key topics in gastroenterology, metabolism, hematology, oncology, and infectious diseases. Students explore anatomy and physiology as well as the diagnosis, prevention, and treatment of relevant diseases. At the same time, the connection to medical informatics is deepened: medical knowledge is to be used, for example, to analyze medical records in a structured manner and to better understand IT challenges in hospitals.
Programming 2 builds on the fundamentals covered in Programming 1 and delves deeper into object-oriented software development. Topics include recursion, generic programming, containers, exception handling, graphical user interfaces, threads and synchronization, as well as file and stream processing. Students develop complete programs of small to medium scope and learn to analyze requirements, create designs, use appropriate development tools, and systematically test software.
This module covers the fundamentals of relational databases and their practical application in information systems. Students learn to develop data models, structure databases, and query them using SQL. Topics such as normal forms, transactions, ACID properties, and indexes are covered, as is practical database programming. The goal is to design and implement database systems for complex applications and to use them with appropriate programming interfaces.
This module provides a basic understanding of operating systems and computer networks as the technical foundation of modern information systems. Topics covered include processes and threads, user and permission management, file systems, as well as network architectures and communication protocols such as IP, TCP, UDP, and DNS. Hands-on exercises with Windows and Linux systems, as well as network components, complement the theoretical content and lay the groundwork for working with complex IT infrastructures.
Analysis 1 covers the mathematical fundamentals required for numerous applications in computer science and medical informatics. Topics include functions, limits, continuity, differential and integral calculus, and basic numerical methods. Students learn to describe mathematical relationships, model real-world problems, and solve them systematically. In addition, function graphs and mathematical models are visualized using tools such as MATLAB or Python.
Stochastics covers the fundamentals of probability theory and statistics, which are of central importance for the analysis of medical data. The course covers descriptive statistics, random variables, discrete and continuous distributions, and the basics of statistical testing. In addition, data sets are analyzed using statistical software. Students learn to identify random components, develop appropriate statistical models, and systematically evaluate, interpret, and graphically represent data.
Building on Analysis 1, this module delves deeper into mathematical methods for more complex applications in information technology. Topics include Taylor and Fourier series, the discrete and fast Fourier transforms, differential equations, numerical methods, and multidimensional analysis. Students learn to model dynamic systems, apply numerical algorithms, and mathematically solve multidimensional problems such as extreme value problems or linearizations.
This module provides a basic understanding of the structures, legal framework, and economic processes in the healthcare sector. Key topics include hospital organization, financing, governance structures, patient management, and relevant legal principles. In addition, business and legal issues are examined. As a result, students develop an understanding of the organizational context in which medical information systems are used and data is processed.
Technical English prepares students for international communication in the field of medical informatics. Using topics from medicine and information technology, the course focuses on developing specialized vocabulary, listening and reading comprehension, discussion, presentation, and written communication skills. Topics include, among others, medical informatics, clinical trials, data management, and medical ethics. The goal is to enable students to use English confidently and flexibly in academic and professional settings at the C1 level.
This module provides an introduction to the technical fundamentals of medical devices and measurement methods. Topics covered include biopotentials, medical sensor technology, and selected medical devices such as vital signs monitors, ventilators, dialysis systems, and heart-lung machines. Students learn how medical measurement data is generated, the characteristics and limitations of the methods, and how this data can be technically analyzed. Practical laboratory exercises combine medical fundamentals with computational methods.
This module provides a comprehensive overview of information systems in the healthcare sector. Topics covered include hospital information systems, patient management, surgical and diagnostic documentation, PACS, practice information systems, and electronic patient and health records. Another focus is on interoperability and standards such as HL7/FHIR, DICOM, XML, and EDIFACT. Students learn to analyze complex information systems, describe requirements, and understand the possibilities for their integration and communication.
This module covers key concepts and methods for efficient data processing. It focuses on algorithms for searching, sorting, and solving graph-based problems, as well as fundamental data structures such as lists, hash tables, and search trees. Students learn to analyze algorithms in terms of correctness and runtime, select appropriate methods, and develop their own efficient solutions for more complex problems.
In this module, programming skills are applied to practical applications in data science and web development. Students work with Python, Jupyter Notebooks, and appropriate libraries for data analysis and visualization. In addition, the module covers the fundamentals of developing dynamic web applications, database integration, and client-server concepts. The goal is for students to independently design, implement, and test data analysis processes and web-based application systems.
Data and Process Modeling teaches methods for the structured description of information structures and workflows. Students work with XML, JSON, CSV, and other data formats, as well as with BPMN for process modeling. The course also covers the fundamentals of data warehousing. Using case studies from the healthcare sector, students learn to analyze data and processes, model them formally, and identify opportunities for optimization.
This module covers the specific requirements for data protection and information security in the healthcare sector. In addition to the legal and ethical foundations, the module focuses on the protection of health data, data protection management, technical and organizational measures, as well as risks and protection needs. Students learn to apply data protection requirements to specific medical scenarios and to develop appropriate protective measures. In addition, the module covers the fundamentals of cryptography, encryption, and digital signatures.
This module teaches methods and tools for the professional planning, management, and implementation of projects. Students learn about project phases, roles, and responsibilities, and explore both traditional and agile methodologies such as Scrum and Kanban. Projects are structured using planning tools such as Gantt charts and network diagrams. The goal is to organize projects in a goal-oriented manner, coordinate teams, and systematically manage and evaluate project progress.
This seminar teaches fundamental skills for conducting academic work in the field of medical informatics. Students learn to conduct targeted research on specialized topics, critically evaluate sources, structure academic texts, and cite them correctly. They develop their own research questions, write an academic paper, and present their findings in English. In addition, students will develop presentation, communication, and time-management skills that are relevant both for their studies and for their future professional careers.
E-health refers to the digital transformation of the healthcare system and encompasses medical, organizational, legal, and technical issues. This module covers the fundamentals of e-health architectures, interoperability, IT standards, data protection, and data security, as well as Germany’s digitalization strategy. Using concrete examples such as telematics infrastructure, electronic health records, and digital identities, students learn to understand and evaluate e-health systems and to assess their potential applications.
This module covers fundamental machine learning methods and their practical application using Python. Topics include supervised and unsupervised learning methods, model evaluation, data preprocessing, regression, classification, clustering, and ensemble methods. The module also includes an introduction to neural networks and deep learning. Students learn to select appropriate algorithms for specific problems, prepare data, and develop, evaluate, and interpret models in a structured manner.
In the project work, students work in teams on a more challenging computer science project, applying the technical and methodological skills they have acquired so far. The projects may address a medical application context and are carried out using a distribution of roles typical in professional practice. In addition to technical implementation, the focus is on project planning, requirements management, agile work methods, version control, and teamwork. This allows students to gain experience that directly prepares them for future professional activities.
Software Engineering teaches systematic methods for developing high-quality application systems. The course covers process models, requirements engineering, UML, object-oriented design, design patterns, and software architectures. The curriculum also includes quality assurance, testing methods, usability, and configuration and version management. Students learn to analyze requirements in a structured manner, design complex software systems, and methodically plan and validate development processes.
In the practical project, students apply the knowledge they have acquired during their studies in a practical semester lasting at least 100 days. They work on real-world tasks at an IT company or an IT-related organization or department. This allows them to deepen their technical knowledge, gain practical experience, and further develop their own areas of focus. At the same time, they become familiar with business processes and put their technical and methodological skills to the test in a professional setting.
The practicum semester project documents and reflects on the experiences gained during the practicum semester. Students prepare a written report and present their activities, insights, and findings to their fellow students. In doing so, they learn to systematically analyze technical and medical contexts from everyday clinical practice, draw conclusions, and present content in a clear and understandable manner. The subsequent discussion also promotes professional reflection and the exchange of different practical experiences.
The bachelor’s thesis marks the academic and professional culmination of the degree program. Students work independently on a clearly defined problem within a specific area of medical informatics, applying engineering or scientific methods. This includes the development and evaluation of solution concepts, the structured execution of a large-scale project, the documentation of results, and their final presentation and technical discussion.