59,479 research outputs found
Enhancing the Guidance of the Intentional Model "MAP": Graph Theory Application
The MAP model was introduced in information system engineering in order to
model processes on a flexible way. The intentional level of this model helps an
engineer to execute a process with a strong relationship to the situation of
the project at hand. In the literature, attempts for having a practical use of
maps are not numerous. Our aim is to enhance the guidance mechanisms of the
process execution by reusing graph algorithms. After clarifying the existing
relationship between graphs and maps, we improve the MAP model by adding
qualitative criteria. We then offer a way to express maps with graphs and
propose to use Graph theory algorithms to offer an automatic guidance of the
map. We illustrate our proposal by an example and discuss its limitations.Comment: 9 page
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Computerization of workflows, guidelines and care pathways: a review of implementation challenges for process-oriented health information systems
There is a need to integrate the various theoretical frameworks and formalisms for modeling clinical guidelines, workflows, and pathways, in order to move beyond providing support for individual clinical decisions and toward the provision of process-oriented, patient-centered, health information systems (HIS). In this review, we analyze the challenges in developing process-oriented HIS that formally model guidelines, workflows, and care pathways. A qualitative meta-synthesis was performed on studies published in English between 1995 and 2010 that addressed the modeling process and reported the exposition of a new methodology, model, system implementation, or system architecture. Thematic analysis, principal component analysis (PCA) and data visualisation techniques were used to identify and cluster the underlying implementation ‘challenge’ themes. One hundred and eight relevant studies were selected for review. Twenty-five underlying ‘challenge’ themes were identified. These were clustered into 10 distinct groups, from which a conceptual model of the implementation process was developed. We found that the development of systems supporting individual clinical decisions is evolving toward the implementation of adaptable care pathways on the semantic web, incorporating formal, clinical, and organizational ontologies, and the use of workflow management systems. These architectures now need to be implemented and evaluated on a wider scale within clinical settings
A service oriented approach for guidelines-based clinical decision support using BPMN
Evidence-based medical practice requires that clinical guidelines need to be documented in such a way that they represent a clinical workflow in its most accessible form. In order to optimize clinical processes to improve clinical outcomes, we propose a Service Oriented Architecture (SOA) based approach for implementing clinical guidelines that can be accessed from an Electronic Health Record (EHR) application with a Web Services enabled communication mechanism with the Enterprise Service Bus. We have used Business Process Modelling Notation (BPMN) for modelling and presenting the clinical pathway in the form of a workflow. The aim of this study is to produce spontaneous alerts in the healthcare workflow in the diagnosis of Chronic Obstructive Pulmonary Disease (COPD). The use of BPMN as a tool to automate clinical guidelines has not been previously employed for providing Clinical Decision Support (CDS)
Knowledge-Intensive Processes: Characteristics, Requirements and Analysis of Contemporary Approaches
Engineering of knowledge-intensive processes (KiPs) is far from being mastered, since they are genuinely knowledge- and data-centric, and require substantial flexibility, at both design- and run-time. In this work, starting from a scientific literature analysis in the area of KiPs and from three real-world domains and application scenarios, we provide a precise characterization of KiPs. Furthermore, we devise some general requirements related to KiPs management and execution. Such requirements contribute to the definition of an evaluation framework to assess current system support for KiPs. To this end, we present a critical analysis on a number of existing process-oriented approaches by discussing their efficacy against the requirements
Fuzzy Logic in Clinical Practice Decision Support Systems
Computerized clinical guidelines can provide significant benefits to health outcomes and costs, however, their effective implementation presents significant problems. Vagueness and ambiguity inherent in natural (textual) clinical guidelines is not readily amenable to formulating automated alerts or advice. Fuzzy logic allows us to formalize the treatment of vagueness in a decision support architecture. This paper discusses sources of fuzziness in clinical practice guidelines. We consider how fuzzy logic can be applied and give a set of heuristics for the clinical guideline knowledge engineer for addressing uncertainty in practice guidelines. We describe the specific applicability of fuzzy logic to the decision support behavior of Care Plan On-Line, an intranet-based chronic care planning system for General Practitioners
Beyond Physical Connections: Tree Models in Human Pose Estimation
Simple tree models for articulated objects prevails in the last decade.
However, it is also believed that these simple tree models are not capable of
capturing large variations in many scenarios, such as human pose estimation.
This paper attempts to address three questions: 1) are simple tree models
sufficient? more specifically, 2) how to use tree models effectively in human
pose estimation? and 3) how shall we use combined parts together with single
parts efficiently?
Assuming we have a set of single parts and combined parts, and the goal is to
estimate a joint distribution of their locations. We surprisingly find that no
latent variables are introduced in the Leeds Sport Dataset (LSP) during
learning latent trees for deformable model, which aims at approximating the
joint distributions of body part locations using minimal tree structure. This
suggests one can straightforwardly use a mixed representation of single and
combined parts to approximate their joint distribution in a simple tree model.
As such, one only needs to build Visual Categories of the combined parts, and
then perform inference on the learned latent tree. Our method outperformed the
state of the art on the LSP, both in the scenarios when the training images are
from the same dataset and from the PARSE dataset. Experiments on animal images
from the VOC challenge further support our findings.Comment: CVPR 201
Population variability in animal health: Influence on dose-exposure-response relationships: Part II: Modelling and simulation
During the 2017 Biennial meeting, the American Academy of Veterinary Pharmacology and Therapeutics hosted a 1‐day session on the influence of population variability on dose‐exposure‐response relationships. In Part I, we highlighted some of the sources of population variability. Part II provides a summary of discussions on modelling and simulation tools that utilize existing pharmacokinetic data, can integrate drug physicochemical characteristics with species physiological characteristics and dosing information or that combine observed with predicted and in vitro information to explore and describe sources of variability that may influence the safe and effective use of veterinary pharmaceuticals
Model and Integrate Medical Resource Available Times and Relationships in Verifiably Correct Executable Medical Best Practice Guideline Models (Extended Version)
Improving patient care safety is an ultimate objective for medical
cyber-physical systems. A recent study shows that the patients' death rate is
significantly reduced by computerizing medical best practice guidelines. Recent
data also show that some morbidity and mortality in emergency care are directly
caused by delayed or interrupted treatment due to lack of medical resources.
However, medical guidelines usually do not provide guidance on medical resource
demands and how to manage potential unexpected delays in resource availability.
If medical resources are temporarily unavailable, safety properties in existing
executable medical guideline models may fail which may cause increased risk to
patients under care. The paper presents a separately model and jointly verify
(SMJV) architecture to separately model medical resource available times and
relationships and jointly verify safety properties of existing medical best
practice guideline models with resource models being integrated in. The SMJV
architecture allows medical staff to effectively manage medical resource
demands and unexpected resource availability delays during emergency care. The
separated modeling approach also allows different domain professionals to make
independent model modifications, facilitates the management of frequent
resource availability changes, and enables resource statechart reuse in
multiple medical guideline models. A simplified stroke scenario is used as a
case study to investigate the effectiveness and validity of the SMJV
architecture. The case study indicates that the SMJV architecture is able to
identify unsafe properties caused by unexpected resource delays.Comment: full version, 12 page
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