Multi-agent model of hepatitis C virus infection

ObjectivesThe objective of this study is to design a method for modeling hepatitis C virus (HCV) infection using multi-agent simulation and to verify it in practice.Methods and materialsIn this paper, first, the modeling of HCV infection using a multi-agent system is compared with the most commonly used model type, which is based on differential equations. Then, the implementation and results of the model using a multi-agent simulation is presented. To find the values of the parameters used in the model, a method using inverted simulation flow and genetic algorithm is proposed. All of the data regarding HCV infection are taken from the paper describing the model based on the differential equation to which the proposed method is compared.ResultsImportant advantages of the proposed method are noted and demonstrated: these include flexibility, clarity, re-usability and the possibility to model more complex dependencies. Then, the simulation framework that uses the proposed approach is successfully implemented in C++ and is verified by comparing it to the approach based on differential equations. The verification proves that an objective function that performs the best is the function that minimizes the maximal differences in the data. Finally, an analysis of one of the already known models is performed, and it is proved that it incorrectly models a decay in the hepatocytes number by 40%.ConclusionsThe proposed method has many advantages in comparison to the currently used model types and can be used successfully for analyzing HCV infection. With almost no modifications, it can also be used for other types of viral infections.     

信息共享联盟模型研究及其在农业领域的应用

本文提出了一种信息共享联盟模型UIS,对模型的结构、功能框架以及相关核心技术,包括异构数据库的标准化处理、URI远程访问技术、快速查询算法等进行了详细讨论.UIS的一个重要特点是:在逻辑上将各个信息资源的异构数据连接在一起,在物理上则对加盟数据按照元数据规范标准进行整合,并备份上传至联盟.该模型通过多主体协作,能够有效地整合异构、分散的数据库,实现信息资源的有效共享和有效检索.模型服务提供了多种模式的信息检索接口.对于已经共享的多媒体资源,通过引入颌域专家的知识问答命题来引导用户的学习,由此实现了教与学之间的互动,提高用户的学习质量.目前UIS已在中国农村科技信息网中进行实验和应用,实现了包括位于北京的"中国现代农业科技信息共享示范网"、"九亿网"、"国家农业科技园区网"等多家网站在内的数据库资源的信息共享,并且在河北省进行了试点,初步建立了中国农业信息共享联盟体系.     

生态流行病学研究设计与统计分析策略

大数据生态流行病学理论范式阐明了一个更全面的生态流行病学视角,承认和捕捉现实世界和虚拟世界中的众多健康决定因素具有等级镶嵌和交互博弈的复杂网络特征。在这种镶嵌分层相互作用及其网络博弈的复杂背景下,传统的基于独立随机假设的传统流行病学抽样调查方法、传统分析流行病学和实验流行病学设计策略及统计分析方法,均面临巨大挑战。取而代之的是,系统动力学模型、网络分析及网络动力学模型、多智能体系统模型以及未来需要发展的生态流行病学超图因果推断模型。从而,由新理论范式、新设计策略和新统计方法,构成了大数据生态流行病学理论方法体系。     

Using a multi-agent system approach for microaneurysm detection in fundus images

ObjectiveMicroaneurysms represent the first sign of diabetic retinopathy, and their detection is fundamental for the prevention of vision impairment. Despite several research attempts to develop an automated system to detect microaneurysms in fundus images, none has shown the level of performance required for clinical practice. We propose a new approach, based on a multi-agent system model, for microaneurysm segmentation.Methods and materialsA multi-agent based approach, preceded by a preprocessing phase to allow construction of the environment in which agents are situated and interact, is presented. The proposed method is applied to two available online datasets and results are compared to other previously described approaches.ResultsMicroaneurysm segmentation emerges from agent interaction. The final score of the proposed approach was 0.240 in the Retinopathy Online Challenge.ConclusionsWe achieved competitive results, primarily in detecting microaneurysms close to vessels, compared to more conventional algorithms. Despite these results not being optimum, they are encouraging and reveal that some improvements may be made.     

Agent技术在Web服务中的应用探讨

Web服务是一组采用面向服务的体系架构的基于标准的Web协议的软件构件,而Agent是一种在某个环境中自主行动以实现其设计目标的智能化软件实体.Web服务与多Agent系统(MAS,Multi-Agent System)在架构、范例和技术方法等方面具有很大的相似性.Web服务的可信性是未来计算机软件发展关键的问题,实现Web服务在分布式环境下的协同式测试具有一定的挑战性.本文在探讨Web服务与Agent技术的共性的基础上,分析并总结了Agent技术在Web服务中的应用.针对Web服务测试的开放性、协同性、动态性和不确定性等特点,结合Agent系统的自主性、反应性、适应性和社会性,本文提出了一种基于MAS的Web服务测试框架(MAST,Multi-Agent-based Service Testing),并对其关键技术进行了探讨.     

Agents endowed with uncertainty management behaviors to solve a multiskill healthcare task scheduling

Health organizations are complex to manage due to their dynamic processes and distributed hospital organization. It is therefore necessary for healthcare institutions to focus on this issue to deal with patients’ requirements. We aim in this paper to develop and implement a management decision support system (DSS) that can help physicians to better manage their organization and anticipate the feature of overcrowding. Our objective is to optimize the Pediatric Emergency Department (PED) functioning characterized by stochastic arrivals of patients leading to its services overload. Human resources allocation presents additional complexity related to their different levels of skills and uncertain availability dates. So, we propose a new approach for multi-healthcare task scheduling based on a dynamic multi-agent system. Decisions about assignment and scheduling are the result of a cooperation and negotiation between agents with different behaviors. We therefore define the actors involved in the agents’ coalition to manage uncertainties related to the scheduling problem and we detail their behaviors. Agents have the same goal, which is to enhance care quality and minimize long waiting times while respecting degrees of emergency. Different visits to the PED services and regular meetings with the medical staff allowed us to model the PED architecture and identify the characteristics and different roles of the healthcare providers and the diverse aspects of the PED activities. Our approach is integrated in a DSS for the management of the Regional University Hospital Center (RUHC) of Lille (France). Our survey is included in the French National Research Agency (ANR) project HOST (Hôpital: Optimisation, Simulation et évitement des Tensions (ANR-11-TecSan-010: http://host.ec-lille.fr/wp-content/themes/twentyeleven/docsANR/R0/HOST-WP0.pdf)).     

Local recurrence and distant metastasis of supratentorial primitive neuro-ectodermal tumor in an adult patient successfully treated with intensive induction chemotherapy and maintenance temozolomide

Supratentorial primitive neuro-ectodermal tumors (PNET) in adults are very rare. Extraneural metastasis are unusual and the optimal palliative chemotherapy regimen is not established. We present a 26-year-old patient with local recurrence and distant metastasis of supratentorial PNET successfully treated with intensive induction chemotherapy and maintenance temozolomide.     

Multi-agent systems simulating the physiological role of plasmic membrane

This paper presents our multi-agent framework for modelling and simulating the physiological role of plasmic membrane specially the 'endocytosis by receptors' and the 'exocytosis' mechanisms. As the dysfunction of a plasmic membrane may cause several illnesses (the family hypercholesterolemia, the dilation and the permeability of blood vessel, the allergic reactions as the asthma, rums of hays, hives, etc.), the objective of our multi-agent framework is to be a virtual world of cellular and molecular biology while simulating the physiological role of plasmic membrane in order to help its specialists to better understand, to good interpret and to warn changes of cell interaction and cell adaptation with its environment via its plasmic membrane. The architecture of our multi-agent framework is composed of a set of reactive agents. These agents use an ontology (named OntoCell) to communicate and to represent their knowledge. OntoCell describes the knowledge of cellular biology. Our framework is implemented with a multi-agent platform (named DIMA).     

Knowledge construction from time series data using a collaborative exploration system

This paper deals with the exploration of biomedical multivariate time series to construct typical parameter evolution or scenarios. This task is known to be difficult: the temporal and multivariate nature of the data at hand and the context-sensitive aspect of data interpretation hamper the formulation of a priori knowledge about the kind of patterns that can be detected as well as their interrelations. This paper proposes a new way to tackle this problem based on a human–computer collaborative approach involving specific annotations. Three grounding principles, namely autonomy, adaptability and emergence, support the co-construction of successive abstraction levels for data interpretation. An agent-based design is proposed to support these principles. Preliminary results in a clinical context are presented to support our proposal. A comparison with two well-known time series exploration tools is furthermore performed.