Artificial Intelligence and Image Processing
By integrating Artificial Intelligence (AI) and image processing in medical technology, diagnosis, treatment, and monitoring of diseases can be improved. Various sensor technologies and evaluation methods are used to recognize and interpret patterns in medical images. The challenge lies in ensuring the reliability and accuracy of these technologies, especially in the face of complex environmental conditions and the lack of available data. Through innovative technologies and systematic analyses of specific use cases, more precise and efficient results should be achieved, ultimately leading to better patient care.
Data Privacy in Data Donations
Effective data protection is essential to safeguard the privacy of data donors and ensure trust in data-based systems and research. Innovative methods such as anonymization, pseudonymization, differential privacy, and homomorphic encryption are used to protect sensitive data while maintaining their value for analysis and research. The focus is on the seamless integration of data protection measures into the development process, also known as Privacy by Design. The combination of these techniques and approaches contributes to achieving a balanced relationship between protecting the privacy of data donors and promoting data-driven innovations, particularly in the field of artificial intelligence. This allows for improved diagnosis, treatment, and monitoring of diseases, while preserving the privacy of patients.
Anomaly Detection at Engine Test Stands
The examination of extensive data sets in technical applications offers the opportunity to optimize work processes and reveal problematic cases early on. In engine tests, the analysis of large amounts of data helps engineers reduce their workload while simultaneously preventing potentially dangerous accidents. The systematic evaluation of test data thus plays a crucial role in the further development of technologies and assists experts in tackling complex challenges in various application areas.
|Impact of differential privacy procedures in data protection on the quality of trained AI models.
|ab 06 / 2023