Deep Learning Techniques Revolutionizing Biomedical Applications

Abstract

Deep learning techniques have revolutionized biomedical applications such as arrhythmia detection, analysis of cardiac sensed signals, and cell-free synthetic biology. This chapter provides an introduction to each topic, discusses the role of deep learning techniques, highlights recent advancements, and explores the challenges and future directions in these areas. It also provides an introduction to cardiac sensed signals and their relevance in cardiology and explores the role of deep learning in analyzing and interpreting cardiac signals. Cell-free synthetic biology is also discussed, including applications in gene circuit design and metabolic engineering. Deep learning techniques are increasingly being used in biomedical applications and are important for personalized medicine, explainability and interpretability, real-time monitoring and intervention, adaptive optimization, and integration with other technologies.