Medicine in words and numbers: a cross-sectional survey comparing probability assessment scales

Contains fulltext : 56355.pdf ( ) (Open Access)Background / In the complex domain of medical decision making, reasoning under uncertainty can benefit from supporting tools. Automated decision support tools often build upon mathematical models, such as Bayesian networks. These networks require probabilities which often have to be assessed by experts in the domain of application. Probability response scales can be used to support the assessment process. We compare assessments obtained with different types of response scale. Methods / General practitioners (GPs) gave assessments on and preferences for three different probability response scales: a numerical scale, a scale with only verbal labels, and a combined verbal-numerical scale we had designed ourselves. Standard analyses of variance were performed. Results / No differences in assessments over the three response scales were found. Preferences for type of scale differed: the less experienced GPs preferred the verbal scale, the most experienced preferred the numerical scale, with the groups in between having a preference for the combined verbal-numerical scale. Conclusion / We conclude that all three response scales are equally suitable for supporting probability assessment. The combined verbal-numerical scale is a good choice for aiding the process, since it offers numerical labels to those who prefer numbers and verbal labels to those who prefer words, and accommodates both more and less experienced professionals.8 p

Complications of hip arthroscopy

Medicine and health care are currently faced with a significant rise in their complexity. This is partly due to the progress made during the past three decades in the fundamental biological understanding of the causes of health and disease at the molecular, (sub)cellular, and organ level. Since the end of the 1970s, when knowledge representation and reasoning in the biomedical field became a separate area of research, huge progress has been made in the development of methods and tools that are finally able to impact on the way medicine is being practiced. Even though there are huge differences in the techniques and methods used by biomedical researchers, there is now an increasing tendency to share research results in terms of formal knowledge representation methods, such as ontologies, statistical models, network models, and mathematical models. As there is an urgent need for health-care professionals to make better decisions, computer-based support using this knowledge is now becoming increasingly important. It may also be the only way to integrate research results from the different parts of the spectrum of biomedical and clinical research. The aim of this book is to shed light on developments in knowledge representation at different levels of biomedical application, ranging from human biology to clinical guidelines, and using different techniques, from probability theory and differential equations to logic. The book starts with two introductory chapters followed by 18 contributions organized in the following topical sections: diagnosis of disease; monitoring of health and disease and conformance; assessment of health and personalization; prediction and prognosis of health and disease; treatment of disease; and recommendations

Quality checking of medical guidelines through logical abduction

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ExpExpExplosion: Uniform Interpolation in General EL Terminologies.

Although εL is a popular logic used in large existing knowledge bases, to the best of our knowledge no procedure has yet been proposed that computes uniform εL interpolants of general εL terminologies. Up to now, also the bounds on the size of uniform εL interpolants remain unknown. In this paper, we propose an approach based on proof theory and the theory of formal tree languages to computing a finite uniform interpolant for a general εL terminology if it exists. Further, we show that, if such a finite uniform εL interpolant exists, then there exists one that is at most triple exponential in the size of the original TBox, and that, in the worst-case, no shorter interpolants exist, thereby establishing the triple exponential tight bounds on their size. © 2012 The Author(s)

Validation of ACCESS: an automated tool to support self-management of COPD exacerbations

Lonneke M Boer,1 Maarten van der Heijden,2 Nathalie ME van Kuijk,1 Peter JF Lucas,2 Jan H Vercoulen,3,4 Willem JJ Assendelft,1 Erik W Bischoff,1 Tjard R Schermer1,5 1Department of Primary and Community Care, Radboud university medical center, Radboud Institute for Health Sciences, Nijmegen, the Netherlands; 2Department of Computing Sciences, Radboud University, Nijmegen, the Netherlands; 3Department of Medical Psychology, Radboud university medical center, Radboud Institute for Health Sciences, Nijmegen, the Netherlands; 4Department of Pulmonary Diseases, Radboud university medical center, Radboud Institute for Health Sciences, Nijmegen, the Netherlands; 5Netherlands Institute for Health Services Research (NIVEL), Utrecht, the Netherlands Background: To support patients with COPD in their self-management of symptom worsening, we developed Adaptive Computerized COPD Exacerbation Self-management Support (ACCESS), an innovative software application that provides automated treatment advice without the interference of a health care professional. Exacerbation detection is based on 12 symptom-related yes-or-no questions and the measurement of peripheral capillary oxygen saturation (SpO2), forced expiratory volume in one second (FEV1), and body temperature. Automated treatment advice is based on a decision model built by clinical expert panel opinion and Bayesian network modeling. The current paper describes the validity of ACCESS. Methods: We performed secondary analyses on data from a 3-month prospective observational study in which patients with COPD registered respiratory symptoms daily on diary cards and measured SpO2, FEV1, and body temperature. We examined the validity of the most important treatment advice of ACCESS, ie, to contact the health care professional, against symptom- and event-based exacerbations. Results: Fifty-four patients completed 2,928 diary cards. One or more of the different pieces of ACCESS advice were provided in 71.7% of all cases. We identified 115 symptom-based exacerbations. Cross-tabulation showed a sensitivity of 97.4% (95% CI 92.0–99.3), specificity of 65.6% (95% CI 63.5–67.6), and positive and negative predictive value of 13.4% (95% CI 11.2–15.9) and 99.8% (95% CI 99.3–99.9), respectively, for ACCESS’ advice to contact a health care professional in case of an exacerbation. Conclusion: In many cases (71.7%), ACCESS gave at least one self-management advice to lower symptom burden, showing that ACCES provides self-management support for both day-to-day symptom variations and exacerbations. High sensitivity shows that if there is an exacerbation, ACCESS will advise patients to contact a health care professional. The high negative predictive value leads us to conclude that when ACCES does not provide the advice to contact a health care professional, the risk of an exacerbation is very low. Thus, ACCESS can safely be used in patients with COPD to support self-management in case of an exacerbation. Keywords: COPD, exacerbations, telehealth, software application, treatment advice, self-management, health, mobile health, automated device, diagnostic accurac

Applying Bayesian networks for intelligent adaptable printing systems

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Exception diagnosis in multiagent contract executions

We propose a diagnosis procedure that agents can use to explain exceptions to contract executions. Contracts are expressed by social commitments associated with temporal constraints. The procedure reasons from the relations among such commitments, and returns one amongst different possible mismatches that may have caused an exception. In particular, we consider two possibilities: misalignment, when two agents have two different views of the same commitment, and misbehavior, when there is no misalignment, but a debtor agent fails to oblige. We also provide a realignment policy that can be applied in case of a misalignment. Our formalization uses a reactive form of Event Calculus. We illustrate the workings of our approach by discussing a delivery process from e-commerce as a case study