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Abstract
Der Bereich Praktika, Projekte, Seminare umfasst Lehrveranstaltungen in unterschiedlichen Formaten zum Erwerb von praktischen Kenntnissen und Fertigkeiten. Ausserdem soll selbstständiges Experimentieren und Gestalten gefördert, exploratives Lernen ermöglicht und die Methodik von Projektarbeiten vermittelt werden.
Objective
Recent biotechnological advances enable high-throughput, low-cost, and accurate biological data generation (e.g., using genome sequencing, multimodal medical imaging, continuous wearable sensing). This wealth of data offers unique opportunities to advance healthcare. These opportunities include, but are not limited to, precision medicine, bedside personalized care, discovering early warning signs of communicable diseases, continuous physiological tracking, and enhanced diagnostic capabilities. Despite these opportunities, efficiently analyzing large-scale biological data poses significant challenges for conventional computing systems. These systems often cannot keep up with the high-throughput rate at which data is generated, and they face additional constraints related to energy efficiency, scalability, privacy, and security. To facilitate the wide adoption of recent advances in healthcare, there is a need to optimize the computing systems to enable high-performance, energy-efficient, low-cost, private, and secure analysis of biological data. This course will focus on identifying key computational challenges in health-related applications and discussing how computer architecture and science can contribute to advancing healthcare by addressing these challenges. First, we will provide seminar lectures that summarize (i) current research approaches in computing system designs for healthcare applications and (ii) new trends and bottlenecks in data-intensive healthcare applications. Second, we will suggest practical projects that enable the students to observe these challenges and bottlenecks and focus on optimizing existing methods or innovating new solutions.