Tracking Dengue Epidemics using Twitter Content Classification and Topic Modelling

Detecting and preventing outbreaks of mosquito-borne diseases such as Dengue and Zika in Brasil and other tropical regions has long been a priority for governments in affected areas. Streaming social media content, such as Twitter, is increasingly being used for health vigilance applications such as flu detection. However, previous work has not addressed the complexity of drastic seasonal changes on Twitter content across multiple epidemic outbreaks. In order to address this gap, this paper contrasts two complementary approaches to detecting Twitter content that is relevant for Dengue outbreak detection, namely supervised classification and unsupervised clustering using topic modelling. Each approach has benefits and shortcomings. Our classifier achieves a prediction accuracy of about 80\% based on a small training set of about 1,000 instances, but the need for manual annotation makes it hard to track seasonal changes in the nature of the epidemics, such as the emergence of new types of virus in certain geographical locations. In contrast, LDA-based topic modelling scales well, generating cohesive and well-separated clusters from larger samples. While clusters can be easily re-generated following changes in epidemics, however, this approach makes it hard to clearly segregate relevant tweets into well-defined clusters.Comment: Procs. SoWeMine - co-located with ICWE 2016. 2016, Lugano, Switzerlan

Alexandria: Extensible Framework for Rapid Exploration of Social Media

The Alexandria system under development at IBM Research provides an extensible framework and platform for supporting a variety of big-data analytics and visualizations. The system is currently focused on enabling rapid exploration of text-based social media data. The system provides tools to help with constructing "domain models" (i.e., families of keywords and extractors to enable focus on tweets and other social media documents relevant to a project), to rapidly extract and segment the relevant social media and its authors, to apply further analytics (such as finding trends and anomalous terms), and visualizing the results. The system architecture is centered around a variety of REST-based service APIs to enable flexible orchestration of the system capabilities; these are especially useful to support knowledge-worker driven iterative exploration of social phenomena. The architecture also enables rapid integration of Alexandria capabilities with other social media analytics system, as has been demonstrated through an integration with IBM Research's SystemG. This paper describes a prototypical usage scenario for Alexandria, along with the architecture and key underlying analytics.Comment: 8 page

Protocol for the effective feedback to improve primary care prescribing safety (EFIPPS) study : a cluster randomised controlled trial using ePrescribing data

High-risk prescribing in primary care is common and causes considerable harm. Feedback interventions to improve care are attractive because they are relatively cheap to widely implement. There is good evidence that feedback has small to moderate effects, but the most recent Cochrane review called for more high-quality, large trials that explicitly test different forms of feedback. The study is a three-arm cluster-randomised trial with general practices being randomised and outcomes measured at patient level. 262 practices in three Scottish Health Board areas have been randomised (94% of all possible practices). The two active arms receive different forms of prescribing safety data feedback, with rates of high-risk prescribing compared with a ‘usual care’ arm. Sample size estimation used baseline data from participating practices. With 85 practices randomised to each arm, then there is 93% power to detect a 25% difference in the percentage of high-risk prescribing (from 6.1% to 4.5%) between the usual care arm and each intervention arm. The primary outcome is a composite of six high-risk prescribing measures (antipsychotic prescribing to people aged ≥75 years; non-steroidal anti-inflammatory drug (NSAID) prescribing to people aged ≥75 without gastroprotection; NSAID prescribing to people prescribed aspirin/clopidogrel without gastroprotection; NSAID prescribing to people prescribed an ACE inhibitor/angiotensin receptor blocker and a diuretic; NSAID prescription to people prescribed an oral anticoagulant without gastroprotection; aspirin/clopidogrel prescription to people prescribed an oral anticoagulant without gastroprotection). The primary analysis will use multilevel modelling to account for repeated measurement of outcomes in patients clustered within practices. The study was reviewed and approved by the NHS Tayside Committee on Medical Research Ethics B (11/ES/0001). The study will be disseminated via a final report to the funder with a publicly available research summary, and peer reviewed publications

Which "industrial policies" are meaningful for Latin America?

This paper’s main concern is to assess which "industrial policies" would be meaningful for Latin America nowadays. The first section considers definitions of "industrial policies" and their nature in the past. The second section centers on national growth experiences that may serve as paradigms for LAC economies. Section 3 is on economies which are growth paradigms and on their relevant policies. Section 4 is on present multilateral constraints on "industrial policies", especially in the case of subsidies and trade-related investment measures, as these have been considerably tightened as a result of the Uruguay Round of multilateral trade negotiations. The following section analyses the link between macroeconomics and "industrial policies" both in relation to limitations imposed by macroeconomic instability on industrial policy and to how growth depends on the cost of investment on both micro and macroeconomic factors. Section 6 analyses industrial policy alternatives. The paper concludes with section 7 which is on policy recommendations seeking to improve criteria to pick winners where market failures are especially costly.

The AURORA pilot study for molecular screening of patients with advanced breast cancer–a study of the breast international group

Several studies have demonstrated the feasibility of molecular screening of tumour samples for matching patients with cancer to targeted therapies. However, most of them have been carried out at institutional or national level. Herein, we report on the pilot phase of AURORA (NCT02102165), a European multinational collaborative molecular screening initiative for advanced breast cancer patients. Forty-one patients were prospectively enroled at four participating centres across Europe. Metastatic tumours were biopsied and profiled using an Ion Torrent sequencing platform at a central facility. Sequencing results were obtained for 63% of the patients in real-time with variable turnaround time stemming from delays between patient consent and biopsy. At least one clinically actionable mutation was identified in 73% of patients. We used the Illumina sequencing technology for orthogonal validation and achieved an average of 66% concordance of substitution calls per patient. Additionally, copy number aberrations inferred from the Ion Torrent sequencing were compared to single nucleotide polymorphism arrays and found to be 59% concordant on average. Although this study demonstrates that powerful next generation genomic techniques are logistically ready for international molecular screening programs in routine clinical settings, technical challenges remain to be addressed in order to ensure the accuracy and clinical utility of the genomic data.info:eu-repo/semantics/publishe

A study of the influence of the socieconomic background of the nursing student on attitude toward selected nursing activities

Thesis (M.S.)--Boston UniversityThis study was undertaken to determine the influence of socio-economic background of nursing students upon attitude toward selected nursing activities. The review of literature suggested that there may be a relationship between socio-economic background and student attitudes. The sample chosen for study was composed of fifteen junior students in a medical-surgical nursing class of a basic collegiate school of nursing. A tool was developed to elicit attitudes about twenty-seven commonly performed nursing activities. Socio-economic background factors were obtained by collecting data pertinent to occupational classification of the father, age of the student, number of siblings, previous work experience in a hospital, participation in household tasks, and number and kind of employed household help. This information was analyzed in relation to the students' expressed attitudes toward the selected nursing activities [TRUNCATED