An online belief rule-based group clinical decision support system

Around ten percent of patients admitted to National Health Service (NHS) hospitals have experienced a patient safety incident, and an important reason for the high rate of patient safety incidents is medical errors. Research shows that appropriate increase in the use of clinical decision support systems (CDSSs) could help to reduce medical errors and result in substantial improvement in patient safety. However several barriers continue to impede the effective implementation of CDSSs in clinical settings, among which representation of and reasoning about medical knowledge particularly under uncertainty are areas that require refined methodologies and techniques. Particularly, the knowledge base in a CDSS needs to be updated automatically based on accumulated clinical cases to provide evidence-based clinical decision support. In the research, we employed the recently developed belief Rule-base Inference Methodology using the Evidential Reasoning approach (RIMER) for design and development of an online belief rule-based group CDSS prototype. In the system, belief rule base (BRB) was used to model uncertain clinical domain knowledge, the evidential reasoning (ER) approach was employed to build inference engine, a BRB training module was developed for learning the BRB through accumulated clinical cases, and an online discussion forum together with an ER-based group preferences aggregation tool were developed for providing online clinical group decision support.We used a set of simulated patients in cardiac chest pain provided by our research collaborators in Manchester Royal Infirmary to validate the developed online belief rule-based CDSS prototype. The results show that the prototype can provide reliable diagnosis recommendations and the diagnostic performance of the system can be improved significantly after training BRB using accumulated clinical cases.EThOS - Electronic Theses Online ServiceManchester Business SchoolGBUnited Kingdo

Clinical decision support systems: A review on knowledge representation and inference under uncertainties

This paper provides a literature review in clinical decision support systems (CDSSs) with a focus on the way knowledge bases are constructed, and how inference mechanisms and group decision making methods are used in CDSSs. Particular attention is paid to the uncertainty handling capability of the commonly used knowledge representation and inference schemes. The definition of what constitute good CDSSs and how they can be evaluated and validated are also considered. Some future research directions for handling uncertainties in CDSSs are proposed

Clinical Decision Support Systems: a Review of Knowledge Representation and Inference under Uncertainties

This paper provides a literature review in clinical decision support systems (CDSSs) with a focus on the way knowledge bases are constructed, and how inference mechanisms and group decision making methods are used in CDSSs. Particular attention is paid to the uncertainty handling capability of the commonly used knowledge representation and inference schemes. The definition of what constitute good CDSSs and how they can be evaluated and validated are also considered. Some future research directions for handling uncertainties in CDSSs are proposed

CHST7 Methylation Status Related to the Proliferation and Differentiation of Pituitary Adenomas

Pituitary adenomas (PAs) are the second most common primary brain tumor and may develop from any of the cell lineages responsible for producing the different pituitary hormones. DNA methylation is one of the essential epigenetic mechanisms in cancers, including PAs. In this study, we measured the expression profile and promoter methylation status of carbohydrate sulfotransferase 7 (CHST7) in patients with PA; then, we investigated the effect of the CHST7 methylation status on the proliferation and differentiation of PAs. The volcano map and Metascape results showed that the levels of CHST7 were related to the lineages’ differentiation and the cell adhesion of PAs, and patients with low CHST7 had greater chances of having an SF-1 lineage (p = 0.002) and optic chiasm compression (p = 0.007). Reactome pathway analysis revealed that most of the DEGs involved in the regulation of TP53 regulated the transcription of cell cycle genes (HSA-6791312 and HSA6804116) in patients with high CHST7. Correlation analysis showed that CHST7 was significantly correlated with the eIF2/ATF4 pathway and mitochondrion-related genes. The AUC of ROC showed that CHST7 (0.288; 95% CI: 0.187–0.388) was superior to SF-1 (0.555; 95% CI: 0.440–0.671) and inferior to FSHB (0.804; 95% CI: 0.704–0.903) in forecasting the SF-1 lineage (p < 0.001). The SF-1 lineage showed a higher methylation frequency for CHST7 than the Pit-1 and TBX19 lineages (p = 0.009). Furthermore, as the key molecule of the hypothalamic–pituitary–gonadal axis, inhibin βE (INHBE) was positively correlated with the levels of CHST7 (r = 0.685, p < 0.001). In summary, CHST7 is a novel pituitary gland specific protein in SF-1 lineage adenomas with a potential role in gonadotroph cell proliferation and lineage differentiation in PAs

Bilayer dissolving microneedle array containing 5-fluorouracil and triamcinolone with biphasic release profile for hypertrophic scar therapy

Hypertrophic scar (HS) is an undesirable skin abnormality following deep burns or operations. Although intralesional multi-injection with the suspension of triamcinolone acetonide (TA) and 5-fluorouracil (5-Fu) has exhibited great promise to HS treatment in clinical, the difference of metabolic behavior between TA and 5-Fu remarkably compromised the treatment efficacy. Besides, the traditional injection with great pain is highly dependent on the skill of the experts, which results in poor compliance. Herein, a bilayer dissolving microneedle (BMN) containing TA and 5-Fu (TA-5-Fu-BMN) with biphasic release profile was designed for HS therapy. Equipped with several micro-scale needle tips, the BMN could be self-pressed into the HS with uniform drug distribution and less pain. Both in vitro permeation and in vivo HS retention tests revealed that TA and 5-Fu could coexist in the scar tissue for a sufficient time period due to the well-designed biphasic release property. Subsequently, the rabbit ear HS model was established to assess therapeutic efficacy. The histological analysis showed that TA-5-Fu-BMN could significantly reduce abnormal fibroblast proliferation and collagen fiber deposition. It was also found that the value of scar elevation index was ameliorated to a basal level, together with the downregulation of mRNA and protein expression of Collagen I (Col I) and transforming growth factor-β1 (TGF-β1) after application of TA-5-Fu-BMN. In conclusion, the BMN with biphasic release profiles could serve as a potential strategy for HS treatment providing both convenient administrations as well as controlled drug release behavior

A belief rule-based decision support system for clinical risk assessment of cardiac chest pain

This paper describes a prototype clinical decision support system (CDSS) for risk stratification of patients with cardiac chest pain. A newly developed belief rule-based inference methodology-RIMER was employed for developing the prototype. Based on the belief rule-based inference methodology, the prototype CDSS can deal with uncertainties in both clinical domain knowledge and clinical data. Moreover, the prototype can automatically update its knowledge base via a belief rule base (BRB) learning module which can adjust BRB through accumulated historical clinical cases. The domain specific knowledge used to construct the knowledge base of the prototype was learned from real patient data. We simulated a set of 1000 patients in cardiac chest pain to validate the prototype. The belief rule-based prototype CDSS has been found to perform extremely well. Firstly, the system can provide more reliable and informative diagnosis recommendations than manual diagnosis using traditional rules when there are clinical uncertainties. Secondly, the diagnostic performance of the system can be significantly improved after training the BRB through accumulated clinical cases. (C) 2011 Elsevier BY. All rights reserved.ManagementOperations Research & Management ScienceSCI(E)EI0ARTICLE3564-57321

Interface engineered in situ anchoring of Co9S8 nanoparticles into a multiple doped carbon matrix : highly efficient zinc – air batteries

Interface modification is an effective and promising route for developing functional electrocatalysts. However, researchers have not created a reliable method to optimize the interfaces of components existing in electrocatalysts, although it is very crucial for the technological development of high-performance electrodes. Here, we develop a strategy aiming at the in situ anchorage of Co9S8 nanoparticles into a nitrogen (N), sulfur (S) co-implanted three-dimensional carbon matrix (Co9S8@NSCM) as a highly active and durable nonprecious metal electrocatalyst for the oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) in alkaline medium. This strategy offers an opportunity to optimize the interface interaction and affords high activity for the ORR and OER in terms of low overpotentials and high current intensities. In addition, by confining Co9S8 nanoparticles into a N,S-doped carbon matrix, corrosion and aggregation can be effectively prevented, and thus the catalyst exhibits nearly unfading ORR catalytic performance after 100 000 s testing, a low discharge–charge voltage gap (0.81 V) and a long cycle life (up to 840 cycles) in Zn–air batteries. The present work highlights potentially powerful interface engineering for designing multi-component heterostructures with advanced performances in oxygen electrochemistry and related energy conversion