XML-Based Image Annotation: PAIS - a Personal Annotated Image Server

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Secure and scalable deduplication of horizontally partitioned health data for privacy-preserving distributed statistical computation

Background Techniques have been developed to compute statistics on distributed datasets without revealing private information except the statistical results. However, duplicate records in a distributed dataset may lead to incorrect statistical results. Therefore, to increase the accuracy of the statistical analysis of a distributed dataset, secure deduplication is an important preprocessing step. Methods We designed a secure protocol for the deduplication of horizontally partitioned datasets with deterministic record linkage algorithms. We provided a formal security analysis of the protocol in the presence of semi-honest adversaries. The protocol was implemented and deployed across three microbiology laboratories located in Norway, and we ran experiments on the datasets in which the number of records for each laboratory varied. Experiments were also performed on simulated microbiology datasets and data custodians connected through a local area network. Results The security analysis demonstrated that the protocol protects the privacy of individuals and data custodians under a semi-honest adversarial model. More precisely, the protocol remains secure with the collusion of up to N − 2 corrupt data custodians. The total runtime for the protocol scales linearly with the addition of data custodians and records. One million simulated records distributed across 20 data custodians were deduplicated within 45 s. The experimental results showed that the protocol is more efficient and scalable than previous protocols for the same problem. Conclusions The proposed deduplication protocol is efficient and scalable for practical uses while protecting the privacy of patients and data custodians

Lessons Learned From the Design and Implementation of Myocardial Infarction Adjudication Tailored for HIV Clinical Cohorts

We developed, implemented, and evaluated a myocardial infarction (MI) adjudication protocol for cohort research of human immunodeficiency virus. Potential events were identified through the centralized Centers for AIDS Research Network of Integrated Clinical Systems data repository using MI diagnoses and/or cardiac enzyme laboratory results (1995–2012). Sites assembled de-identified packets, including physician notes and results from electrocardiograms, procedures, and laboratory tests. Information pertaining to the specific antiretroviral medications used was redacted for blinded review. Two experts reviewed each packet, and a third review was conducted if discrepancies occurred. Reviewers categorized probable/definite MIs as primary or secondary and identified secondary causes of MIs. The positive predictive value and sensitivity for each identification/ascertainment method were calculated. Of the 1,119 potential events that were adjudicated, 294 (26%) were definite/probable MIs. Almost as many secondary (48%) as primary (52%) MIs occurred, often as the result of sepsis or cocaine use. Of the patients with adjudicated definite/probable MIs, 78% had elevated troponin concentrations (positive predictive value = 57%, 95% confidence interval: 52, 62); however, only 44% had clinical diagnoses of MI (positive predictive value = 45%, 95% confidence interval: 39, 51). We found that central adjudication is crucial and that clinical diagnoses alone are insufficient for ascertainment of MI. Over half of the events ultimately determined to be MIs were not identified by clinical diagnoses. Adjudication protocols used in traditional cardiovascular disease cohorts facilitate cross-cohort comparisons but do not address issues such as identifying secondary MIs that may be common in persons with human immunodeficiency virus

A systematic review on integration mechanisms in human and animal health surveillance systems with a view to addressing global health security threats

Lymphatic filariasis and onchocerciasis are neglected tropical diseases (NTDs) targeted for elimination by mass (antifilarial) drug administration. These drugs are predominantly active against the microfilarial progeny of adult worms. New drugs or combinations are needed to improve patient therapy and to enhance the effectiveness of interventions in persistent hotspots of transmission. Several therapies and regimens are currently in (pre-)clinical testing. Clinical trial simulators (CTSs) project patient outcomes to inform the design of clinical trials but have not been widely applied to NTDs, where their resource-saving payoffs could be highly beneficial. We demonstrate the utility of CTSs using our individual-based onchocerciasis transmission model (EPIONCHO-IBM) that projects trial outcomes of a hypothetical macrofilaricidal drug. We identify key design decisions that influence the power of clinical trials, including participant eligibility criteria and post-treatment follow-up times for measuring infection indicators. We discuss how CTSs help to inform target product profiles

Sustainable development and human resource management. A science mapping approach

Financiación ECO2017-82208-PThis manuscript presents a systematic review of "sustainable human resource man-agement"(HRM), highlighting its major themes and the evolution and tendenciesobserved in this field. It contributes to the development of this relatively new topic,offering a critical evaluation and identifying the highest impact research strands.The Web of Science database returned 111 documents spanning the period 1997-2018, and a conceptual science mapping analysis based on co-word bibliographic net-works was developed, using SciMAT as an analytical tool. The motor themes (welldeveloped and important for the structure of the discipline) in the field of sustainableHRM areenvironmental management,socially responsible HRM, andturnover.Employeeengagementis a specialised theme (well developed but less important for the struc-ture of the research field),human resource practicesis a basic or transversal theme(important for the discipline but not developed), andsustainable leadershipandenvi-ronmental performanceare emerging themes (both weakly developed and marginalto the field).Management and Marketing Department (University of Pablo de Olavide

Association of Immunosuppression and Human Immunodeficiency Virus (HIV) Viremia with Anal Cancer Risk in Persons Living with HIV in the United States and Canada

Background: People living with human immunodeficiency virus (HIV; PLWH) have a markedly elevated anal cancer risk, largely due to loss of immunoregulatory control of oncogenic human papillomavirus infection. To better understand anal cancer development and prevention, we determined whether recent, past, cumulative, or nadir/peak CD4+ T-cell count (CD4) and/or HIV-1 RNA level (HIV RNA) best predict anal cancer risk. Methods: We studied 102 777 PLWH during 1996-2014 from 21 cohorts participating in the North American AIDS Cohort Collaboration on Research and Design. Using demographics-adjusted, cohort-stratified Cox models, we assessed associations between anal cancer risk and various time-updated CD4 and HIV RNA measures, including cumulative and nadir/peak measures during prespecified moving time windows. We compared models using the Akaike information criterion. Results: Cumulative and nadir/peak CD4 or HIV RNA measures from approximately 8.5 to 4.5 years in the past were generally better predictors for anal cancer risk than their corresponding more recent measures. However, the best model included CD4 nadir (ie, the lowest CD4) from approximately 8.5 years to 6 months in the past (hazard ratio [HR] for <50 vs ≥500 cells/μL, 13.4; 95% confidence interval [CI], 3.5-51.0) and proportion of time CD4 <200 cells/μL from approximately 8.5 to 4.5 years in the past (a cumulative measure; HR for 100% vs 0%, 3.1; 95% CI, 1.5-6.6). Conclusions: Our results are consistent with anal cancer promotion by severe, prolonged HIV-induced immunosuppression. Nadir and cumulative CD4 may represent useful markers for identifying PLWH at higher anal cancer risk

IML: An image markup language.

Image Markup Language is an extensible markup language (XML) schema used to describe both image metadata and annotations. It describes both data pertaining to an entire image, and data that are tied to specific regions or features of the image. Developed for a specific domain in Medical Education, this pa-per describes extensions to take advantage of the Dublin Core metadata standard, and of an XML schema for vector graphics representation. We have developed a prototype system of open source tools implementing an authoring system, a client system, and an image annotation database which can be queried though the Web