CardioML: integrating personal cardiac information for ubiquous diagnosis and analysis

The latest medical diagnosis devices enable the performance of e-diagnosis making the access to these services easier, faster and available in remote areas. However this imposes new communications and data interchange challenges. In this paper a new XML based format for storing cardiac signals and related information is presented. The proposed structure encompasses data acquisition devices, patient information, data description, pathological diagnosis and waveform annotation. When compared with similar purpose formats several advantages arise. Besides the full integrated data model it may also be noted the available geographical references for e-diagnosis, the multi stream data description, the ability to handle several simultaneous devices, the possibility of independent waveform annotation and a HL7 compliant structure for common contents. These features represent an enhanced integration with existent systems and an improved flexibility for cardiac data representation.

Machine Learning Algorithms at Myocardial Perfusion Imaging - a Preliminary Study

Introduction: A major focus of data mining process - especially machine learning researches - is to automatically learn to recognize complex patterns and help to take the adequate decisions strictly based on the acquired data. Since imaging techniques like MPI – Myocardial Perfusion Imaging on Nuclear Cardiology, can implicate a huge part of the daily workflow and generate gigabytes of data, there could be advantages on Computerized Analysis of data over Human Analysis: shorter time, homogeneity and consistency, automatic recording of analysis results, relatively inexpensive, etc.Objectives: The aim of this study relates with the evaluation of the efficacy of this methodology on the evaluation of MPI Stress studies and the process of decision taking concerning the continuation – or not – of the evaluation of each patient. It has been pursued has an objective to automatically classify a patient test in one of three groups: “Positive”, “Negative” and “Indeterminate”. “Positive” would directly follow to the Rest test part of the exam, the “Negative” would be directly exempted from continuation and only the “Indeterminate” group would deserve the clinician analysis, so allowing economy of clinician’s effort, increasing workflow fluidity at the technologist’s level and probably sparing time to patients. Methods: WEKA v3.6.2 open source software was used to make a comparative analysis of three WEKA algorithms (“OneR”, “J48” and “Naïve Bayes”) - on a retrospective study using the comparison with correspondent clinical results as reference, signed by nuclear cardiologist experts - on “SPECT Heart Dataset”, available on University of California – Irvine, at the Machine Learning Repository. For evaluation purposes, criteria as “Precision”, “Incorrectly Classified Instances” and “Receiver Operating Characteristics (ROC) Areas” were considered. Results: The interpretation of the data suggests that the Naïve Bayes algorithm has the best performance among the three previously selected algorithms. Conclusions: It is believed - and apparently supported by the findings - that machine learning algorithms could significantly assist, at an intermediary level, on the analysis of scintigraphic data obtained on MPI, namely after Stress acquisition, so eventually increasing efficiency of the entire system and potentially easing both roles of Technologists and Nuclear Cardiologists. In the actual continuation of this study, it is planned to use more patient information and significantly increase the population under study, in order to allow improving system accuracy.

Immunohistochemical molecular phenotypes of gastric cancer based on SOX2 and CDX2 predict patient outcome

Background Gastric cancer remains a serious health concern worldwide. Patients would greatly benefit from the discovery of new biomarkers that predict outcome more accurately and allow better treatment and follow-up decisions. Here, we used a retrospective, observational study to assess the expression and prognostic value of the transcription factors SOX2 and CDX2 in gastric cancer. Methods SOX2, CDX2, MUC5AC and MUC2 expression were assessed in 201 gastric tumors by immunohistochemistry. SOX2 and CDX2 expression were crossed with clinicopathological and follow-up data to determine their impact on tumor behavior and outcome. Moreover, SOX2 locus copy number status was assessed by FISH (N = 21) and Copy Number Variation Assay (N = 62). Results SOX2 was expressed in 52% of the gastric tumors and was significantly associated with male gender, T stage and N stage. Moreover, SOX2 expression predicted poorer patient survival, and the combination with CDX2 defined two molecular phenotypes, SOX2+CDX2- versus SOX2-CDX2+, that predict the worst and the best long-term patients’ outcome. These profiles combined with clinicopathological parameters stratify the prognosis of patients with intestinal and expanding tumors and in those without signs of venous invasion. Finally, SOX2 locus copy number gains were found in 93% of the samples reaching the amplification threshold in 14% and significantly associating with protein expression. Conclusions We showed, for the first time, that SOX2 combined with CDX2 expression profile in gastric cancer segregate patients into different prognostic groups, complementing the clinicopathological information. We further demonstrate a molecular mechanism for SOX2 expression in a subset of gastric cancer cases.

Knowledge and technologies in innovative information systems

7th Mediterranean Conference on Information Systems, MCIS 2012, Guimaraes, Portugal, September 8-10, 2012, Proceedings Series: Lecture Notes in Business Information Processing, Vol. 129

Efeitos de um programa de educação para a saúde no doente portador de DPOC

Objectivo: Verificar o efeito de um programa de educação para a saúde em doentes portadores de DPOC. Metodologia: Estudo experimental (ensaio clínico) com 18 doentes portadores de DPOC seleccionados aleatoriamente através da consulta de Medicina Geral e Familiar. Depois de informar os objectivos do estudo e os aspectos éticos, os participantes realizaram uma avaliação da função pulmonar, capacidade de tolerância ao exercício, qualidade de vida, actividades de vida diária (AVD), dispneia e ansiedade e depressão. Posteriormente os indivíduos do grupo controlo receberam um manual informativo e os incluídos no grupo experimental além de receber o manual foram submetidos a 6 sessões de educação. Após 8 semanas todos os doentes foram reavaliados. O nível de significância utilizado nos testes estatísticos foi α=0.05 (intervalo de confiança de 95%). Resultados: A análise da diferença dos ganhos entre os grupos revelou-se estatisticamente significativa nas variáveis qualidade de vida (p<0,001), AVD (p<0,001) e depressão (p<0,001). Na capacidade de tolerância ao exercício ambos os grupos melhoraram significativamente mas a diferença de ganhos não foi estatisticamente significativa (p=0,289), tal como na variável ansiedade (p=0,960). Conclusão: Este estudo parece demonstrar que o programa de educação foi eficaz nas variáveis qualidade de vida, AVD e depressão.

VPPs information needs for effective operation in competitive electricity markets

The large increase of renewable energy sources and Distributed Generation (DG) of electricity gives place to the Virtual Power Producer (VPP) concept. VPPs may turn electricity generation by renewable sources valuable in electricity markets. Information availability and adequate decision-support tools are crucial for achieving VPPs’ goals. This involves information concerning associated producers and market operation. This paper presents ViProd, a simulation tool that allows simulating VPPs operation, focusing mainly in the information requirements for adequate decision making.

Decision support system with incomplete and domain incoherent information management

Many of the most common human functions such as temporal and non-monotonic reasoning have not yet been fully mapped in developed systems, even though some theoretical breakthroughs have already been accomplished. This is mainly due to the inherent computational complexity of the theoretical approaches. In the particular area of fault diagnosis in power systems however, some systems which tried to solve the problem, have been deployed using methodologies such as production rule based expert systems, neural networks, recognition of chronicles, fuzzy expert systems, etc. SPARSE (from the Portuguese acronym, which means expert system for incident analysis and restoration support) was one of the developed systems and, in the sequence of its development, came the need to cope with incomplete and/or incorrect information as well as the traditional problems for power systems fault diagnosis based on SCADA (supervisory control and data acquisition) information retrieval, namely real-time operation, huge amounts of information, etc. This paper presents an architecture for a decision support system, which can solve the presented problems, using a symbiosis of the event calculus and the default reasoning rule based system paradigms, insuring soft real-time operation with incomplete, incorrect or domain incoherent information handling ability. A prototype implementation of this system is already at work in the control centre of the Portuguese Transmission Network.

A study on dynamic state information (DSI) around users for safe urban life

To select each node by devices and by contexts in urban computing, users have to put their plan information and their requests into a computing environment (ex. PDA, Smart Devices, Laptops, etc.) in advance and they will try to keep the optimized states between users and the computing environment. However, because of bad contexts, users may get the wrong decision, so, one of the users’ demands may be requesting the good server which has higher security. To take this issue, we define the structure of Dynamic State Information (DSI) which takes a process about security including the relevant factors in sending/receiving contexts, which select the best during user movement with server quality and security states from DSI. Finally, whenever some information changes, users and devices get the notices including security factors, then an automatic reaction can be possible; therefore all users can safely use all devices in urban computing.

Histogram-based DNA analysis for the visualization of chromosome, genome and species information

We describe a novel approach to explore DNA nucleotide sequence data, aiming to produce high-level categorical and structural information about the underlying chromosomes, genomes and species. The article starts by analyzing chromosomal data through histograms using fixed length DNA sequences. After creating the DNA-related histograms, a correlation between pairs of histograms is computed, producing a global correlation matrix. These data are then used as input to several data processing methods for information extraction and tabular/graphical output generation. A set of 18 species is processed and the extensive results reveal that the proposed method is able to generate significant and diversified outputs, in good accordance with current scientific knowledge in domains such as genomics and phylogenetics.

Avaliação da satisfação e importância atribuída aos serviços prestados na área da saúde mental

Com o objectivo de avaliar o grau de satisfação e importância atribuída aos serviços prestados na consulta na área da saúde mental e identificar as relações entre as variáveis demográficas e o grau de satisfação do utente foi realizado um estudo descritivo transversal, numa amostra de 305 utentes. Com a aplicação do questionário verificamos que a satisfação conjugada com a importância fornece-nos informação valiosa permitindo identificar pontos fortes, oportunidades ou necessidades de melhoria dos serviços. Neste estudo verificamos que os utentes encontram-se satisfeitos com os serviços prestados e consideram-nos importantes. Na análise bivariada, encontramos relação entre a satisfação e escolaridade.

Information and communication technologies in education – a web-based intelligent tutoring system on teaching and learning electrical project

Electrical activity is extremely broad and distinct, requiring by one hand, a deep knowledge on rules, regulations, materials, equipments, technical solutions and technologies and assistance in several areas, as electrical equipment, telecommunications, security and efficiency and rational use of energy, on the other hand, also requires other skills, depending on the specific projects to be implemented, being this knowledge a characteristic that belongs to the professionals with relevant experience, in terms of complexity and specific projects that were made.

Analysis and visualization of chromosome information

This paper analyzes the DNA code of several species in the perspective of information content. For that purpose several concepts and mathematical tools are selected towards establishing a quantitative method without a priori distorting the alphabet represented by the sequence of DNA bases. The synergies of associating Gray code, histogram characterization and multidimensional scaling visualization lead to a collection of plots with a categorical representation of species and chromosomes.

Can power laws help us understand gene and proteome information?

Proteins are biochemical entities consisting of one or more blocks typically folded in a 3D pattern. Each block (a polypeptide) is a single linear sequence of amino acids that are biochemically bonded together. The amino acid sequence in a protein is defined by the sequence of a gene or several genes encoded in the DNA-based genetic code. This genetic code typically uses twenty amino acids, but in certain organisms the genetic code can also include two other amino acids. After linking the amino acids during protein synthesis, each amino acid becomes a residue in a protein, which is then chemically modified, ultimately changing and defining the protein function. In this study, the authors analyze the amino acid sequence using alignment-free methods, aiming to identify structural patterns in sets of proteins and in the proteome, without any other previous assumptions. The paper starts by analyzing amino acid sequence data by means of histograms using fixed length amino acid words (tuples). After creating the initial relative frequency histograms, they are transformed and processed in order to generate quantitative results for information extraction and graphical visualization. Selected samples from two reference datasets are used, and results reveal that the proposed method is able to generate relevant outputs in accordance with current scientific knowledge in domains like protein sequence/proteome analysis.

European information users: topics from a comparative analysis within the European Union

Purpose – The aim of this article is to present some results from research undertaken into the information behaviour of European Documentation Centre (EDC) users. It will reflect on the practices of a group of 234 users of 55 EDCs covering 21 Member States of the European Union (EU), used to access European information. Design/methodology/approach – In order to collect the data presented here, five questionnaires were sent to users in all the EDCs in Finland, Ireland, Hungary and Portugal. In the remaining EU countries, five questionnaires were sent to two EDCs chosen at random. The questionnaires were sent by post, following telephone contact with the EDC managers. Findings – Factors determining access to information on the European Union and the frequency of this access are identified. The information providers most commonly used to access European information and the information sources considered the most reliable by respondents will also be analysed. Another area of analysis concerns the factors cited by respondents as facilitating access to information on Europe or, conversely, making it more difficult to access. Parallel to this, the aspects of accessing information on EU that are valued most by users will also be assessed. Research limitations/implications – Questionnaires had to be used, as the intention was to cover a very extensive geographical area. However, in opting for closed questions, it is acknowledged that standard responses have been obtained with no scope for capturing the individual circumstances of each respondent, thus making a qualitative approach difficult. Practical implications – The results provide an overall picture of certain aspects of the information behaviour of EDC users. They may serve as a starting point for planning training sessions designed to develop the skills required to search, access, evaluate and apply European information within an academic context. From a broader perspective, they also constitute factors which the European Commission should take into consideration when formulating its information and communication policy. Originality/value – This is the first piece of academic research into the EDCs and their users, which aimed to cover all Members State of the EU.

Post-surgical wound infections involving Enterobacteriaceae with reduced susceptibility to ß-lactams in two Portuguese hospitals

The post-surgical period is often critical for infection acquisition. The combination of patient injury and environmental exposure through breached skin add risk to pre-existing conditions such as drug or depressed immunity. Several factors such as the period of hospital staying after surgery, base disease, age, immune system condition, hygiene policies, careless prophylactic drug administration and physical conditions of the healthcare centre may contribute to the acquisition of a nosocomial infection. A purulent wound can become complicated whenever antimicrobial therapy becomes compromised. In this pilot study, we analysed Enterobacteriaceae strains, the most significant gram-negative rods that may occur in post-surgical skin and soft tissue infections (SSTI) presenting reduced β-lactam susceptibility and those presenting extended-spectrum β-lactamases (ESBL). There is little information in our country regarding the relationship between β-lactam susceptibility, ESBL and development of resistant strains of microorganisms in SSTI. Our main results indicate Escherichia coli and Klebsiella spp. are among the most frequent enterobacteria (46% and 30% respectively) with ESBL production in 72% of Enterobacteriaceae isolates from SSTI. Moreover, coinfection occurred extensively, mainly with Pseudomonas aeruginosa and Methicillin-resistant Staphylococcus aureus (18% and 13%, respectively). These results suggest future research to explore if and how these associations are involved in the development of antibiotic resistance.