Phenylacetyl-peptide amphiphiles were designed, which upon cleavage by a disease-associated enzyme reconfigure from micellar aggregates to fibres. Upon this morphological change, a doxorubicin payload could be retained in the fibres formed, which makes them valuable carriers for localised formation of nanofibre depots for slow release of hydrophobic anticancer drugs.
Classic navigation using navigational paper charts is being replaced with ECDIS systems, and starting as from 2018, a complete transition to the PLECDIS system as the primary navigational system (eng. Paper – Less Electronic Chart and Display Information System – possessing information system and the display of electronic charts without the obligation of possessing paper […]
Various machine learning techniques have been applied to different problems in survival analysis in the last decade. They were usually adapted to learning from censored survival data by using the information on observation time. This includes learning from parts of the data or interventions to the learning algorithms. Efficient models were established in various fields […]
The completion of ECDIS mandatory implementation period on-board SOLAS vessels requires certain operational, functional and educational gaping holes to be solved. It especially refers to positioning and its redundancy, which represents fundamental safety factor on-board navigating vessels. The proposed paper deals with primary and secondary positioning used in ECDIS system. Standard positioning methods are described, […]
Different survival data pre-processing procedures and adaptations of existing machine-learning techniques have been successfully applied to numerous fields in clinical medicine. Zupan et al. (2000) proposed handling censored survival data by assigning distributions of outcomes to shortly observed censored instances. In this paper, we applied their learning technique to two well-known procedures for learning Bayesian […]
ObjectiveBayesian networks are commonly used for presenting uncertainty and covariate interactions in an easily interpretable way. Because of their efficient inference and ability to represent causal relationships, they are an excellent choice for medical decision support systems in diagnosis, treatment, and prognosis. Although good procedures for learning Bayesian networks from data have been defined, their […]