Abstract
Computerized decision support systems help both health professionals and patients make the right diagnostic and therapeutic decisions in a timely fashion, capitalizing on the available knowledge as well as on data-driven methods. The wealth of data, which have been made available via connected health technologies, the broader uptake of systems biology/medicine, and the technological progress of artificial intelligence are the three pillars leveraging such systems in respiratory care. In addition, for decision support, the following should be considered: (a) the complex interaction of the respiratory system with the circulatory and other systems, (b) the respiratory system decision-making spans in many directions and time scales, in acute and chronic care, and (c) the wealth of informative measurements and signals can contribute in this. This chapter will present methodological analysis for several respiratory disorders, namely sleep apnea, respiratory infections (including the COVID-19 pandemic), chronic lung diseases, and ventilation in respiratory care, including the data and methods applicable in each case.