15 research outputs found
Genetic parameters and selection of Brachiaria decumbens hybrids for agronomic traits and resistance to spittlebugs
Alien plant invasions in tropical and sub-tropical savannas: patterns, processes and prospects
Tropical forage technologies can deliver multiple benefits in Sub-Saharan Africa. A meta-analysis
Computational models in cardiology
The treatment of individual patients in cardiology practice increasingly relies on advanced imaging, genetic screening and devices. As the amount of imaging and other diagnostic data increases, paralleled by the greater capacity to personalize treatment, the difficulty of using the full array of measurements of a patient to determine an optimal treatment seems also to be paradoxically increasing. Computational models are progressively addressing this issue by providing a common framework for integrating multiple data sets from individual patients. These models, which are based on physiology and physics rather than on population statistics, enable computational simulations to reveal diagnostic information that would have otherwise remained concealed and to predict treatment outcomes for individual patients. The inherent need for patient-specific models in cardiology is clear and is driving the rapid development of tools and techniques for creating personalized methods to guide pharmaceutical therapy, deployment of devices and surgical interventions