Enhancing guideline-based decision support with distributed computation through local mobile application

We introduce the need for a distributed guideline-based decision support (DSS) process, describe its characteristics, and explain how we implemented this process within the European Union’s MobiGuide project. In particular, we have developed a mechanism of sequential, piecemeal projection, i.e., 'downloading' small portions of the guideline from the central DSS server, to the local DSS in the patient's mobile device, which then applies that portion, using the mobile device's local resources. The mobile device sends a callback to the central DSS when it encounters a triggering pattern predefined in the projected module, which leads to an appropriate predefined action by the central DSS, including sending a new projected module, or directly controlling the rest of the workflow. We suggest that such a distributed architecture that explicitly defines a dialog between a central DSS server and a local DSS module, better balances the computational load and exploits the relative advantages of the central server and of the local mobile device

Relationships among charges, fields, and potential on spherical surfaces boundary value problems

This paper suggests a new point of view for the Poisson equation and its solution for the potential and field on the d dimensional sphere, Sd, on which point charges are distributed. The available solutions for the potential on multidimensional spheres in the literature are purely mathematical, while the solution suggested here is motivated by physical intuition and requires minimal background; namely, basic laws of electrostatics and dimensional analysis. In this study, the modified Coulomb’s law is presented by means of “dimensional reduction” and the use of equivalence between a point charge on Sd and a charged ray in Rd+1.Besides formal detailed solutions and theorems, this paper presents concrete physical examples (unstudied or studied partly), such as distribution of charges/sources on a two-sphere; Dirichlet problem for currents on a truncated sphere; and fields and potentials created by “infinite” cones. Well-known statements about special charge distributions in Euclidean space must be reformulated and amended when dealing with the case of charges embedded in a spherical manifold

Function of Cancer Associated Genes Revealed by Modern Univariate and Multivariate Association Tests

<div><p>Copy number variation (CNV) plays a role in pathogenesis of many human diseases, especially cancer. Several whole genome CNV association studies have been performed for the purpose of identifying cancer associated CNVs. Here we undertook a novel approach to whole genome CNV analysis, with the goal being identification of associations between CNV of different genes (CNV-CNV) across 60 human cancer cell lines. We hypothesize that these associations point to the roles of the associated genes in cancer, and can be indicators of their position in gene networks of cancer-driving processes. Recent studies show that gene associations are often non-linear and non-monotone. In order to obtain a more complete picture of all CNV associations, we performed omnibus univariate analysis by utilizing dCov, MIC, and HHG association tests, which are capable of detecting any type of association, including non-monotone relationships. For comparison we used Spearman and Pearson association tests, which detect only linear or monotone relationships. Application of dCov, MIC and HHG tests resulted in identification of twice as many associations compared to those found by Spearman and Pearson alone. Interestingly, most of the new associations were detected by the HHG test. Next, we utilized dCov's and HHG's ability to perform multivariate analysis. We tested for association between genes of unknown function and known cancer-related pathways. Our results indicate that multivariate analysis is much more effective than univariate analysis for the purpose of ascribing biological roles to genes of unknown function. We conclude that a combination of multivariate and univariate omnibus association tests can reveal significant information about gene networks of disease-driving processes. These methods can be applied to any large gene or pathway dataset, allowing more comprehensive analysis of biological processes.</p></div

Example of significant relationships.

<p>First line consists of three findings discovered only by Spearman or Pearson; second, only by HHG; third, only by dCov; and fourth, only by MIC. P-values (after adjusting for multiple testing) are denoted in each plot.</p

Euler diagram of the significant discoveries found by Pearson or Spearman, dCov and HHG.

<p>MIC was excluded due to the small number of significant findings provided by this method. The area of each oval represents the number of significant tests of each method, and intersections (emphasized by different colors) represent common discoveries. Evidently, Pearson or Spearman, dCov and HHG share 185 discoveries; 184 tests were significant by HHG but not by Pearson, Spearman or dCov; 10 tests were significant by dCov and not by Pearson, Spearman or HHG; 29 tests were significant by Pearson or Spearman but not by dCov or HHG; dCov and HHG share 26 discoveries; Pearson or Spearman and dCov share 35 discoveries; and Pearson or Spearman and HHG share only 5 discoveries.</p

MobiGuide: a personalized and patient-centric decision-support system and its evaluation in the atrial fibrillation and gestational diabetes domains

MobiGuide is a ubiquitous, distributed and personalized evidence-based decision-support system (DSS) used by patients and their care providers. Its central DSS applies computer-interpretable clinical guidelines (CIGs) to provide real-time patient-specific and personalized recommendations by matching CIG knowledge with a highly-adaptive patient model, the parameters of which are stored in a personal health record (PHR). The PHR integrates data from hospital medical records, mobile biosensors, data entered by patients, and recommendations and abstractions output by the DSS. CIGs are customized to consider the patients’ psycho-social context and their preferences; shared decision making is supported via decision trees instantiated with patient utilities. The central DSS “projects” personalized CIG-knowledge to a mobile DSS operating on the patients’ smart phones that applies that knowledge locally. In this paper we explain the knowledge elicitation and specification methodologies that we have developed for making CIGs patient-centered and enabling their personalization. We then demonstrate feasibility, in two very different clinical domains, and two different geographic sites, as part of a multi-national feasibility study, of the full architecture that we have designed and implemented. We analyze usage patterns and opinions collected via questionnaires of the 10 atrial fibrillation (AF) and 20 gestational diabetes mellitus (GDM) patients and their care providers. The analysis is guided by three hypotheses concerning the effect of the personal patient model on patients and clinicians’ behavior and on patients’ satisfaction. The results demonstrate the sustainable usage of the system by patients and their care providers and patients’ satisfaction, which stems mostly from their increased sense of safety. The system has affected the behavior of clinicians, which have inspected the patients’ models between scheduled visits, resulting in change of diagnosis for two of the ten AF patients and anticipated change in therapy for eleven of the twenty GDM patients