A Tractable Inference Algorithm for Diagnosing Multiple Diseases

We examine a probabilistic model for the diagnosis of multiple diseases. In the model, diseases and findings are represented as binary variables. Also, diseases are marginally independent, features are conditionally independent given disease instances, and diseases interact to produce findings via a noisy OR-gate. An algorithm for computing the posterior probability of each disease, given a set of observed findings, called quickscore, is presented. The time complexity of the algorithm is O(nm-2m+), where n is the number of diseases, m+ is the number of positive findings and m- is the number of negative findings. Although the time complexity of quickscore i5 exponential in the number of positive findings, the algorithm is useful in practice because the number of observed positive findings is usually far less than the number of diseases under consideration. Performance results for quickscore applied to a probabilistic version of Quick Medical Reference (QMR) are provided.Comment: Appears in Proceedings of the Fifth Conference on Uncertainty in Artificial Intelligence (UAI1989

An Approach to Modelling Information System Availability by Using Bayesian Belief Network

In today’s era of the ubiquitous use of information technology (IT), it is expected that the information systems provide services to end-users on continuous basis, regardless of time and location. This is especially true in organizations where information systems (IS) support real-time critical operations, particularly, in the industries in which these systems must continuously operate 24x7x365. This paper presents a modified Bayesian Belief Network model for predicting IS availability. Based on a thorough review of all IS availability dimensions, we proposed a modified set of determinants. The model is parametrized using probability elicitation process with the participation of experts from the BiH financial sector. The results showed that most influential determinants of the IS availability are a timely and precise definition of the availability requirements, quality of IT operations, management and network. This work is licensed under a&nbsp;Creative Commons Attribution-NonCommercial 4.0 International License.</p

Modeling Information System Availability by using Bayesian Belief Network Approach

Modern information systems are expected to be always-on by providing services to end-users, regardless of time and location. This is particularly important for organizations and industries where information systems support real-time operations and mission-critical applications that need to be available on 24 x 7 x 365 basis. Examples of such entities include process industries, telecommunications, healthcare, energy, banking, electronic commerce and a variety of cloud services. This article presents a modified Bayesian Belief Network model for predicting information system availability, introduced initially by Franke, U. and Johnson, P. (in article “Availability of enterprise IT systems – an expert based Bayesian model”. Software Quality Journal 20(2), 369-394, 2012) based on a thorough review of several dimensions of the information system availability, we proposed a modified set of determinants. The model is parameterized by using probability elicitation process with the participation of experts from the financial sector of Bosnia and Herzegovina. The model validation was performed using Monte Carlo simulation

Proceso de elicitación de requerimientos para la construcción de modelos predictivos basados en sistemas inteligentes

¿Cuál opción es la más favorable? ¿Qué nos deparará a futuro? Estas son preguntas que nos hacemos cada vez que tenemos que tomar alguna decisión. Por esta razón, contar con mecanismos que permitan realizar predicciones acertadas es algo que la Humanidad siempre ha querido. Dicha necesidad no es propia únicamente de los individuos y también impacta en las organizaciones. Teniendo en cuenta estas cuestiones, el presente proyecto propone el desarrollo de un proceso que a partir de los deseos y necesidades de una organización, asista a la elicitación de los requerimientos para implementar exitosamente un Modelo Predictivo basado en Sistemas Inteligentes.Eje: Agentes y Sistemas Inteligentes.Red de Universidades con Carreras en Informática (RedUNCI

Cost-Effective Marine Protection - A Pragmatic Approach

This paper puts forward a framework for probabilistic and holistic cost-effectiveness analysis to provide support in selecting the least-cost set of measures to reach a multidimensional environmental objective. Following the principles of ecosystem-based management, the framework includes a flexible methodology for deriving and populating criteria for effectiveness and costs and analyzing complex ecological-economic trade-offs under uncertainty. The framework is applied in the development of the Finnish Programme of Measures (PoM) for reaching the targets of the EU Marine Strategy Framework Directive (MSFD). The numerical results demonstrate that substantial cost savings can be realized from careful consideration of the costs and multiple effects of management measures. If adopted, the proposed PoM would yield improvements in the state of the Baltic Sea, but the overall objective of the MSFD would not be reached by the target year of 2020; for various environmental and administrative reasons, it would take longer for most measures to take full effect.Peer reviewe