Medical guidelines have a significant role in the field of evidence-based medical treatment. The content of a medical guideline is based on a systematic review of clinical evidence with instructions and recommendations that clinicians can refer to. Most of the guidelines are available in an unstructured text format. Hence, clinicians must take a considerable time […]
The fast growing digitalization of medicine has facilitated the collection of patient data in databases. A smart city must facilitate such databases in its hospitals. However, handling this big data requires new strategies for filtering and processing such high volumes of patient data. In this regard, Machine Learning (ML) algorithms are increasingly applied to support […]
Sepsis is one of the leading causes of death in Intensive Care Units (ICU) world-wide. Continuous Petri Nets (CPNs) offer a promising solution in modelling its underlying, complex pathophysiological processes. In this work, we propose a framework to evolve CPNs, i.e. evolve its places, transitions, arc weights, topology, and kinetics. This facilitates modeling complex biological […]
Petri nets (HPNs) that can model biological systems. In particular, based on a state space formulation we develop a decisionaided adaptive gradient descent (DAAGD) algorithm capable of cost-effectively estimating the parameters used in an HPN model. Contrary to standard gradient descent techniques, the DAAGD algorithm does not require prior knowledge, i.e., information about the discrete […]