Knowledge-based modelling applied to synucleinopathies

The adoption of telemedicine technologies has enabled collaborative programs involving a variety of links among distributed medical structures and health officials and professionals. The use for telemedicine for transmission of medical data and the possibility for several distant physicians to share their knowledge on given medical cases provides clear benefits, but also raises several unsolved conceptual and technical challenges. The seamless exchange and access of medical information between medical structures, health professionals, and patients is a prerequisite for the harmonious development of this new medical practice. This paper proposes a new approach of semantic interoperability for enabling mutual understanding of terminologies and concepts used. The proposed semantic interoperability approach is based on conceptual graph to support collaborative activities by describing how different health specialists can apply appropriate strategies to eliminate differential medical diagnosis. Intelligent analysis strategies are used to narrow down and pinpoint medical disorders. The model proposed is fully verified by a case study in the context of elderly patients and specifically dealing with synucleinopathies, a group of neurodegenerative diseases that include Parkinson's disease (PD), dementia with Lewy bodies (DLB), pure autonomic failure (PAF) and multiple system atrophy (MSA)

Focal Spot, Winter 2006/2007

https://digitalcommons.wustl.edu/focal_spot_archives/1104/thumbnail.jp

Conceptual graph-based knowledge representation for supporting reasoning in African traditional medicine

Although African patients use both conventional or modern and traditional healthcare simultaneously, it has been proven that 80% of people rely on African traditional medicine (ATM). ATM includes medical activities stemming from practices, customs and traditions which were integral to the distinctive African cultures. It is based mainly on the oral transfer of knowledge, with the risk of losing critical knowledge. Moreover, practices differ according to the regions and the availability of medicinal plants. Therefore, it is necessary to compile tacit, disseminated and complex knowledge from various Tradi-Practitioners (TP) in order to determine interesting patterns for treating a given disease. Knowledge engineering methods for traditional medicine are useful to model suitably complex information needs, formalize knowledge of domain experts and highlight the effective practices for their integration to conventional medicine. The work described in this paper presents an approach which addresses two issues. First it aims at proposing a formal representation model of ATM knowledge and practices to facilitate their sharing and reusing. Then, it aims at providing a visual reasoning mechanism for selecting best available procedures and medicinal plants to treat diseases. The approach is based on the use of the Delphi method for capturing knowledge from various experts which necessitate reaching a consensus. Conceptual graph formalism is used to model ATM knowledge with visual reasoning capabilities and processes. The nested conceptual graphs are used to visually express the semantic meaning of Computational Tree Logic (CTL) constructs that are useful for formal specification of temporal properties of ATM domain knowledge. Our approach presents the advantage of mitigating knowledge loss with conceptual development assistance to improve the quality of ATM care (medical diagnosis and therapeutics), but also patient safety (drug monitoring)

Health Literacy of Individuals Living with Parkinson\u27s Disease

In the past two decades, there has been an increased interest in the development of self-management programs for people with chronic diseases. Fundamental to chronic disease management is adequate literacy and health literacy skills. Research on the health literacy skills of individuals managing Parkinson’s disease (PD) is seemingly absent from the research literature. The purpose of this study was to assess the health literacy skills of older adults managing PD and to examine the relationships of functional health literacy, self-efficacy, social support, and empowerment in this population. Using a cross-sectional design, this study surveyed 33 older adults living with PD within southwestern Ontario. Functional health literacy was positively correlated with self-efficacy (r=.13) and empowerment (r=.20) in individuals living with PD. As well, there was an association between functional health literacy and social support. Findings suggest that self-efficacy, social support, and empowerment may affect PD patients’ ability to find, read, understand, and communicate health-related information. Keywords: Parkinson’s disease, functional health literacy, self-efficacy, empowerment, social suppor

Combining conceptual graphs and argumentation for aiding in the teleexpertise

Current medical information systems are too complex to be meaningfully exploited. Hence there is a need to develop new strategies for maximising the exploitation of medical data to the benefit of medical professionals. It is against this backdrop that we want to propose a tangible contribution by providing a tool which combines conceptual graphs and Dung׳s argumentation system in order to assist medical professionals in their decision making process. The proposed tool allows medical professionals to easily manipulate and visualise queries and answers for making decisions during the practice of teleexpertise. The knowledge modelling is made using an open application programming interface (API) called CoGui, which offers the means for building structured knowledge bases with the dedicated functionalities of graph-based reasoning via retrieved data from different institutions (hospitals, national security centre, and nursing homes). The tool that we have described in this study supports a formal traceable structure of the reasoning with acceptable arguments to elucidate some ethical problems that occur very often in the telemedicine domain

Lipoprotein ontology as a functional knowledge base

The advances of high throughput research in the biomedical domain have resulted in an onslaught of data being generated at an exponential rate. As a result, researchers face challenges in navigating through overwhelming amounts of information in order to derive relevant scientific insights. Ontologies address these issues by providing explicit description of biomedical entities and a platform for the integration of data, thereby enabling a more efficient retrieval of information. There have been major efforts in the development of biomedical ontologies in the recent years; however no such ontology exists for lipoproteins, which play a crucial role in various biological and cellular functions. Dysregulation in lipoprotein metabolism is significantly associated with an increased risk to cardiovascular disease, the leading cause of mortality in the world today. The aim of this paper is to propose a preliminary framework for Lipoprotein Ontology, with particular focus on the etiology and treatment of lipoprotein dysregulation. This may provide a novel and effective strategy for managing at risk individuals

DiMoPEx-project is designed to determine the impacts of environmental exposure on human health

The WHO has ranked environmental hazardous exposures in the living and working environment among the top risk factors for chronic disease mortality. Worldwide, about 40 million people die each year from noncommunicable diseases (NCDs) including cancer, diabetes, and chronic cardiovascular, neurological and lung diseases. The exposure to ambient pollution in the living and working environment is exacerbated by individual susceptibilities and lifestyle-driven factors to produce complex and complicated NCD etiologies. Research addressing the links between environmental exposure and disease prevalence is key for prevention of the pandemic increase in NCD morbidity and mortality. However, the long latency, the chronic course of some diseases and the necessity to address cumulative exposures over very long periods does mean that it is often difficult to identify causal environmental exposures. EU-funded COST Action DiMoPEx is developing new concepts for a better understanding of health- environment (including gene-environment) interactions in the etiology of NCDs. The overarching idea is to teach and train scientists and physicians to learn how to include efficient and valid exposure assessments in their research and in their clinical practice in current and future cooperative projects. DiMoPEx partners have identified some of the emerging research needs, which include the lack of evidence-based exposure data and the need for human-equivalent animal models mirroring human lifespan and low-dose cumulative exposures. Utilizing an interdisciplinary approach incorporating seven working groups, DiMoPEx will focus on aspects of air pollution with particulate matter including dust and fibers and on exposure to low doses of solvents and sensitizing agents. Biomarkers of early exposure and their associated effects as indicators of disease-derived information will be tested and standardized within individual projects. Risks arising from some NCDs, like pneumoconioses, cancers and allergies, are predictable and preventable. Consequently, preventative action could lead to decreasing disease morbidity and mortality for many of the NCDs that are of major public concern. DiMoPEx plans to catalyze and stimulate interaction of scientists with policy-makers in attacking these exposure-related diseases

Regulatory objectivity in action: Mild cognitive impairment and the collective production of uncertainty

In this paper, we investigate recent changes in the definition and approach to Alzheimer’s disease brought about by growing clinical, therapeutic and regulatory interest in the prodromal or preclinical aspects of this condition. In the last decade, there has been an increased interest in the biomolecular and epidemiological characterization of pre-clinical dementia. It is argued that early diagnosis of dementia, and particularly of Alzheimer‘s disease, will facilitate the prevention of dementing processes and lower the prevalence of the condition in the general population. The search for a diagnostic category or biomarker that would serve this purpose is an ongoing but problematic endeavour for research and clinical communities in this area. In this paper, we explore how clinical and research actors, in collaboration with regulatory institutions and pharmaceutical companies, come to frame these domains as uncertainties and how they re-deploy uncertainty in the ‘collective production’ of new diagnostic conventions and bioclinical standards. While drawing as background on ethnographic, documentary and interview data, the paper proposes an in-depth, contextual analysis of the proceedings of an international meeting organized by the Peripheral and Central Nervous System Drug Advisory Committee of the US Food and Drug Administration to discuss whether or not a particular diagnostic convention — mild cognitive impairment — exists and how best it ought to be studied. Based on this analysis we argue that the deployment of uncertainty is reflexively implicated in bioclinical collectives’ search for rules and conventions, and furthermore that the collective production of uncertainty is central to the ‘knowledge machinery’ of regulatory objectivity