Objective To develop an effective decision tree management model for smart triage of nervous system diseases based on artificial neural networks and Bayesian decision theory. Methods Bayesian decision theory was used as the theoretical basis, and convolutional neural network was used to complete the rapid specialist / sub-specialist machine learning. For the specialist or sub-specialist triage data, circular neural network and Bayesian algorithm were performed to complete the probability distribution and convergence of disease symptoms and diagnosis. Results The decision tree management model and theoretical demonstration were established. According to the characteristics of the transfer learning, the rapid learning of nervous system diseases and accurate triage system, and the remote smart triage system were successfully constructed. Conclusions The management model could provide theoretical references for further use, and alleviate to some extent the currently high rate of outpatient appointment withdrawal and changes.

Ebola virus (EBOV) is a key member of Filoviridae family and causes severe human infectious diseases with high morbidity and mortality. As a typical negative-sense single-stranded RNA (-ssRNA) viruses, EBOV possess a nucleocapsid protein (NP) to facilitate genomic RNA encapsidation to form viral ribonucleoprotein complex (RNP) together with genome RNA and polymerase, which plays the most essential role in virus proliferation cycle. However, the mechanism of EBOV RNP formation remains unclear. In this work, we solved the high resolution structure of core domain of EBOV NP. The polypeptide of EBOV NP core domain (NP(core)) possesses an N-lobe and C-lobe to clamp a RNA binding groove, presenting similarities with the structures of the other reported viral NPs encoded by the members from Mononegavirales order. Most strikingly, a hydrophobic pocket at the surface of the C-lobe is occupied by an α-helix of EBOV NP(core) itself, which is highly conserved among filoviridae family. Combined with other biochemical and biophysical evidences, our results provides great potential for understanding the mechanism underlying EBOV RNP formation via the mobility of EBOV NP element and enables the development of antiviral therapies targeting EBOV RNP formation.
Crystallography, X-Ray ; Ebolavirus ; physiology ; Humans ; Nucleoproteins ; chemistry ; genetics ; metabolism ; Protein Structure, Tertiary ; Structure-Activity Relationship ; Virus Assembly ; physiology