Prediction of future hospital admissions - what is the tradeoff between specificity and accuracy?

Large amounts of electronic medical records collected by hospitals across the developed world offer unprecedented possibilities for knowledge discovery using computer based data mining and machine learning. Notwithstanding significant research efforts, the use of this data in the prediction of disease development has largely been disappointing. In this paper we examine in detail a recently proposed method which has in preliminary experiments demonstrated highly promising results on real-world data. We scrutinize the authors' claims that the proposed model is scalable and investigate whether the tradeoff between prediction specificity (i.e. the ability of the model to predict a wide number of different ailments) and accuracy (i.e. the ability of the model to make the correct prediction) is practically viable. Our experiments conducted on a data corpus of nearly 3,000,000 admissions support the authors' expectations and demonstrate that the high prediction accuracy is maintained well even when the number of admission types explicitly included in the model is increased to account for 98% of all admissions in the corpus. Thus several promising directions for future work are highlighted.Comment: In Proc. International Conference on Bioinformatics and Computational Biology, April 201

FACTORS INFLUENCING STRATEGIC USE OF WEBBASED PLATFORM AND ITS IMPACT ON EDUCATION AT UNIVERSITY

Introducing web-based platforms in education process opens new era of technology for learning including huge challenges in education. Web-based learning could be considered as essential component fostering online learning and teaching. Various factors influencing the teachers while applying study materials in e-learning platform are investigated in the given research study. The author offers an indicative pattern of a standard content of eteaching materials, and investigates to what extent teaching materials available in MOODLE correspond to this standard pattern for ensuring comprehensive web-based e-learning and supporting effective collaboration system for the students and educator. For assessment the completeness level of e-materials available the composite coefficient is recommended as useful tool for educators who are interested in developing e-learning and e-teaching

Methods for prediction of thermally-induced ice loads on dams and hydro-electrical structures

Recommended values of the thermally-induced loads at different locations and climatic zones were primarily obtained on the basis of available empirical values. A review of the literature on the theories and analytical models previously proposed for calculation of the thermally-induced loads on dams and other hydro-electrical structures is presented in this report. The comparison of previously proposed models with measured data showed a wide variation, and none of the available models for predicting ice pressure were capable of predicting the measured pressure within an acceptable margin of error. In Norway, the values of the thermal ice load are suggested to vary between 100 and 150 kN/m. In other countries, such as Canada and USA, the recommended thermal ice loads are higher than in Norway and varies between 150 and 220 kN/m. The maximum thermal ice load measured during laboratory experiment in Sweden was 250 kN/m. This literature study focuses also on current standards and recommendations, in Norway, Sweden, Canada, USA and Russia, for determining thermal ice pressure acting on dams and reservoirs, i.e. methods for the thermally-induced loads or recommended values for an equivalent line load representing the thermal ice pressure.publishedVersio

Contemporary Russian Literature in Latvia: Children’s Literature

Throughout the 20th century, Russian children’s literature in Latvia was a unique phenomenon. Against the background of the general trends of Soviet children’s literature, Latvian children’s literature (in both Latvian and Russian) developed in a space that was less constrained in respect of ideological censorship. 21st century children’s literature in Latvia is developing both taking into account the previous history and current trends. The article is devoted to the specific features of children’s literature in Russian, taking into account the general status of the Russian language as a foreign language and general trends in the socio-cultural space of Latvia. The study considers two main issues. First, it is a sociological analysis of the situation: an assortment of children’s books, the specifics of the school programme, awareness of contemporary Latvian and Russian children’s literature. On the other hand, the corpus of texts of contemporary children’s literature is studied, and an overview of the oeuvre of contemporary Latvian authors is presented. The material for literary analysis was the book by Vladimir Novikov, “The Mischief of the Obedient Martins”. In the course of the analysis, the specifics of the traditional children’s story, the cultural and historical context of the cross-border identity of the author and his potential readers, the specifics of the contemporary narrative, the identification of the concept “one’s own – other’s” were revealed

Automatic knowledge extraction from EHRs

Increasing efforts in the collection, standardization, and maintenance of large scale longitudinal elec- tronic health care records (EHRs) across the world provide a promising source of real world medical data with the potential of providing major novel insights of benefit both to specific individuals in the context of personalized medicine, as well as on the level of population-wide health care and policy. The present paper builds upon the existing and intensifying efforts at using machine learning to provide predictions on future diagnoses likely to be experienced by a particular individual based on the person’s existing diagnostic history. The specific model adopted as the baseline predictive framework is based on the concept of a binary diagnostic history vector representation of a patient’s diagnostic medical record. The technical novelty introduced herein concerns the manner in which transitions between diagnostic history vectors are learnt. We demonstrate that the proposed change prima fasciae enables greater learning specificity. We present a series of experiments which demon- strate the effectiveness of the proposed techniques, and which reveal novel insights regarding the most promising future research directions.Postprin

Towards sophisticated learning from EHRs : increasing prediction specificity and accuracy using clinically meaningful risk criteria

Computer based analysis of Electronic Health Records (EHRs) has the potential to provide major novel insights of benefit both to specific individuals in the context of personalized medicine, as well as on the level of population-wide health care and policy. The present paper introduces a novel algorithm that uses machine learning for the discovery of longitudinal patterns in the diagnoses of diseases. Two key technical novelties are introduced: one in the form of a novel learning paradigm which enables greater learning specificity, and another in the form of a risk driven identification of confounding diagnoses. We present a series of experiments which demonstrate the effectiveness of the proposed techniques, and which reveal novel insights regarding the most promising future research directions.Postprin

In vivo imaging of protease activity by Probody therapeutic activation.

Probody™ therapeutics are recombinant, proteolytically-activated antibody prodrugs, engineered to remain inert until activated locally by tumor-associated proteases. Probody therapeutics exploit the fundamental dysregulation of extracellular protease activity that exists in tumors relative to healthy tissue. Leveraging the ability of a Probody therapeutic to bind its target at the site of disease after proteolytic cleavage, we developed a novel method for profiling protease activity in living animals. Using NIR optical imaging, we demonstrated that a non-labeled anti-EGFR Probody therapeutic can become activated and compete for binding to tumor cells in vivo with a labeled anti-EGFR monoclonal antibody. Furthermore, by inhibiting matriptase activity in vivo with a blocking-matriptase antibody, we show that the ability of the Probody therapeutic to bind EGFR in vivo was dependent on protease activity. These results demonstrate that in vivo imaging of Probody therapeutic activation can be used for screening and characterization of protease activity in living animals, and provide a method that avoids some of the limitations of prior methods. This approach can improve our understanding of the activity of proteases in disease models and help to develop efficient strategies for cancer diagnosis and treatment

ТРАДИЦИЯ И ЛИТЕРАТУРА О ХОЛОКОСТЕ

The notion of literature on Holocaust is rather much debated in contemporary literary science and Judaic studies. Recently two points of view concerning it have emerged. That of Western European literary scholarship suggests the term ‘literature of testimonial’ that regards the events of Holocaust as a climax in the history of human consciousness in line with the related changes regarding artistic creation. The East European and the Near East traditions apply the designation ‘literature on Holocaust’ in relation to works of a certain thematic range, traditionally singling out in a separate group books of memories representing rather memoir material and not works of fiction. The paper will regard the artistic models wherein the theme of Holocaust appears in the background and not in the focus – works by E. Sevela, F. Gorenstein, G. Kanovich. These texts let us talk about search for a new model of a new understanding of the context regarding the theme of Holocaust. Besides, the literary model of these authors has been greatly influenced by their professional activities in cinematography, in particular the cinematographic reflection of the theme of Holocaust built on the crossing point of following the tradition and search for new techniques.KEY WORDS: Holocaust, russian-jewish literature, tradicionally, artistic model

Recovery from Gaming Addiction: A rapid review and thematic synthesis

In recent years the field of gaming addiction has experienced an upsurge in empirical studies on various treatment approaches. Despite the advances in our understanding of how gaming addiction can be treated, the wider concept of recovery continues to be under-researched. The purpose of this review was to explore how individuals addicted to video games experience the process of recovery. Seven databases were systematically searched for qualitative studies. Eight studies representing the views of 225 participants were included in the review. Study findings were exported into NVivo software and analysed using Thematic Synthesis. Six themes were constructed: “developing awareness”, “deciding to change”, “the process of quitting”, “the challenges of quitting”, “recovery never stops” and “treatment for gaming addiction”. Except for the last, themes represent processes that most participants had gone through during recovery, though significant variation was found in how each process was experienced. In addition to overcoming addiction symptoms, recovery involved management of concomitant problems and various negative consequences of excessive gaming. Regarding practice implications, current findings suggest that treatment programs should adopt a multidimensional approach, providing evidence-based treatments, help for co-occurring problems, as well as pre- and post-treatment support to accommodate individuals at different stages of recovery. Further research is needed to expand our understanding of recovery, for instance, the impact of gender differences or how recovery experiences change based on different recovery goals (i.e., abstinence or reduced play time)