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https://www.readbyqxmd.com/read/28507610/improving-patient-safety-in-hospitals-through-usage-of-cloud-supported-video-surveillance
#1
Predrag Dašić, Jovan Dašić, Bojan Crvenković
BACKGROUND: Patient safety in hospitals is of equal importance as providing treatments and urgent healthcare. With the development of Cloud technologies and Big Data analytics, it is possible to employ VSaaS technology virtually anywhere, for any given security purpose. AIM: For the listed benefits, in this paper, we give an overview of the existing cloud surveillance technologies which can be implemented for improving patient safety. MATERIAL AND METHODS: Modern VSaaS systems provide higher elasticity and project scalability in dealing with real-time information processing...
April 15, 2017: Open Access Macedonian Journal of Medical Sciences
https://www.readbyqxmd.com/read/28480477/evaluation-considerations-for-secondary-uses-of-clinical-data-principles-for-an-evidence-based-approach-to-policy-and-implementation-of-secondary-analysis-a-position-paper-from-the-imia-technology-assessment-quality-development-in-health-informatics-working
#2
P J Scott, M Rigby, E Ammenwerth, J Brender McNair, A Georgiou, H Hyppönen, N de Keizer, F Magrabi, P Nykänen, W T Gude, W Hackl
OBJECTIVES: To set the scientific context and then suggest principles for an evidence-based approach to secondary uses of clinical data, covering both evaluation of the secondary uses of data and evaluation of health systems and services based upon secondary uses of data. METHOD: Working Group review of selected literature and policy approaches. RESULTS: We present important considerations in the evaluation of secondary uses of clinical data from the angles of governance and trust, theory, semantics, and policy...
May 8, 2017: Yearbook of Medical Informatics
https://www.readbyqxmd.com/read/28480474/secondary-use-and-analysis-of-big-data-collected-for-patient-care-contribution-from-the-imia-working-group-on-data-mining-and-big-data-analytics
#3
F J Martin-Sanchez, V Aguiar-Pulido, G H Lopez-Campos, N Peek, L Sacchi
OBJECTIVES: To identify common methodological challenges and review relevant initiatives related to the re-use of patient data collected in routine clinical care, as well as to analyze the economic benefits derived from the secondary use of this data. Through the use of several examples, this article aims to provide a glimpse into the different areas of application, namely clinical research, genomic research, study of environmental factors, and population and health services research...
May 8, 2017: Yearbook of Medical Informatics
https://www.readbyqxmd.com/read/28425345/surrogate-marker-analysis-in-cancer-clinical-trials-through-time-to-event-mediation-techniques
#4
Sjouke Vandenberghe, Luc Duchateau, Leen Slaets, Jan Bogaerts, Stijn Vansteelandt
The meta-analytic approach is the gold standard for validation of surrogate markers, but has the drawback of requiring data from several trials. We refine modern mediation analysis techniques for time-to-event endpoints and apply them to investigate whether pathological complete response can be used as a surrogate marker for disease-free survival in the EORTC 10994/BIG 1-00 randomised phase 3 trial in which locally advanced breast cancer patients were randomised to either taxane or anthracycline based neoadjuvant chemotherapy...
January 1, 2017: Statistical Methods in Medical Research
https://www.readbyqxmd.com/read/28423778/developing-healthcare-data-analytics-apps-with-open-data-science-tools
#5
Bibo Hao, Wen Sun, Yiqin Yu, Guotong Xie
Recent advances in big data analytics provide more flexible, efficient, and open tools for researchers to gain insight from healthcare data. Whilst many tools require researchers to develop programs with programming languages like Python, R and so on, which is not a skill set grasped by many researchers in the healthcare data analytics area. To make data science more approachable, we explored existing tools and developed a practice that can help data scientists convert existing analytics pipelines to user-friendly analytics APPs with rich interactions and features of real-time analysis...
2017: Studies in Health Technology and Informatics
https://www.readbyqxmd.com/read/28392994/medical-big-data-promise-and-challenges
#6
Choong Ho Lee, Hyung-Jin Yoon
The concept of big data, commonly characterized by volume, variety, velocity, and veracity, goes far beyond the data type and includes the aspects of data analysis, such as hypothesis-generating, rather than hypothesis-testing. Big data focuses on temporal stability of the association, rather than on causal relationship and underlying probability distribution assumptions are frequently not required. Medical big data as material to be analyzed has various features that are not only distinct from big data of other disciplines, but also distinct from traditional clinical epidemiology...
March 2017: Kidney Research and Clinical Practice
https://www.readbyqxmd.com/read/28388297/cancer-transcriptome-dataset-analysis-comparing-methods-of-pathway-and-gene-regulatory-network-based-cluster-identification
#7
Seungyoon Nam
Cancer transcriptome analysis is one of the leading areas of Big Data science, biomarker, and pharmaceutical discovery, not to forget personalized medicine. Yet, cancer transcriptomics and postgenomic medicine require innovation in bioinformatics as well as comparison of the performance of available algorithms. In this data analytics context, the value of network generation and algorithms has been widely underscored for addressing the salient questions in cancer pathogenesis. Analysis of cancer trancriptome often results in complicated networks where identification of network modularity remains critical, for example, in delineating the "druggable" molecular targets...
April 2017: Omics: a Journal of Integrative Biology
https://www.readbyqxmd.com/read/28384839/semi-automated-de-identification-of-german-content-sensitive-reports-for-big-data-analytics
#8
Hannes Seuss, Peter Dankerl, Matthias Ihle, Andrea Grandjean, Rebecca Hammon, Nicola Kaestle, Peter A Fasching, Christian Maier, Jan Christoph, Martin Sedlmayr, Michael Uder, Alexander Cavallaro, Matthias Hammon
No abstract text is available yet for this article.
April 6, 2017: RöFo: Fortschritte Auf Dem Gebiete der Röntgenstrahlen und der Nuklearmedizin
https://www.readbyqxmd.com/read/28379960/gc-ms-and-proteomics-to-unravel-the-painting-history-of-the-lost-giant-buddhas-of-b%C3%A4-miy%C3%A4-n-afghanistan
#9
Anna Lluveras-Tenorio, Roberto Vinciguerra, Eugenio Galano, Catharina Blaensdorf, Erwin Emmerling, Maria Perla Colombini, Leila Birolo, Ilaria Bonaduce
A chemical investigation of the organic paint binders of the Giant Buddhas of Bāmiyān was performed using an analytical approach based on mass spectrometry, combining traditional gas chromatography/mass spectrometry protocols with advanced proteomics methodologies. The research was carried out on a selection of rescued fragments. The data revealed the use of egg proteins as the paint binders of the original layers, in accordance with the traditional use of this proteinaceous medium in antiquity, spanning from the Mediterranean basin to the Far East, and already in the Bronze Age...
2017: PloS One
https://www.readbyqxmd.com/read/28374205/a-multivariate-approach-for-a-comparison-of-big-data-matrices-case-study-thermo-hygrometric-monitoring-inside-the-carcer-tullianum-rome-in-the-absence-and-in-the-presence-of-visitors
#10
Giovanni Visco, Susanne H Plattner, Patrizia Fortini, Mariapia Sammartino
In the last decades, the very fast improvement of the analytical instrumentation has led to the possibility of quickly and easily getting a lot of data; in turn, the need of advanced statistical methods suitable to extract the full information furnished by instruments has increased. Such kind of data treatments is particularly important in any case of continuous monitoring of one or more parameters, so the microclimate monitoring is a typical example for this application. Microclimate control is essential in the conservation of Cultural Heritage (CH), but decisions on optimal conservation parameters cannot base only on existing norms that do not take into account the environment's history...
April 4, 2017: Environmental Science and Pollution Research International
https://www.readbyqxmd.com/read/28369768/pharma-perspective-on-drug-repurposing
#11
REVIEW
Y Cha, T Erez, I J Reynolds, D Kumar, J Ross, G Koytiger, R Kusko, B Zeskind, S Risso, E Kagan, S Papapetropoulos, I Grossman, D Laifenfeld
Drug repurposing holds the potential to bring medications with known safety profiles to new patient populations. Numerous examples exist for the identification of new indications for existing molecules, most stemming from serendipitous findings or focused recent efforts specifically limited to the mode of action of a specific drug. In recent years, the need for new approaches to drug R&D, combined with the advent of big-data repositories and associated analytics has generated interest in developing systematic approaches to drug repurposing...
March 29, 2017: British Journal of Pharmacology
https://www.readbyqxmd.com/read/28368170/computerized-scoring-algorithms-for-the-autobiographical-memory-test
#12
Keisuke Takano, Charlotte Gutenbrunner, Kris Martens, Karen Salmon, Filip Raes
Reduced specificity of autobiographical memories is a hallmark of depressive cognition. Autobiographical memory (AM) specificity is typically measured by the Autobiographical Memory Test (AMT), in which respondents are asked to describe personal memories in response to emotional cue words. Due to this free descriptive responding format, the AMT relies on experts' hand scoring for subsequent statistical analyses. This manual coding potentially impedes research activities in big data analytics such as large epidemiological studies...
April 3, 2017: Psychological Assessment
https://www.readbyqxmd.com/read/28344853/snap-a-general-purpose-network-analysis-and-graph-mining-library
#13
Jure Leskovec, Rok Sosič
Large networks are becoming a widely used abstraction for studying complex systems in a broad set of disciplines, ranging from social network analysis to molecular biology and neuroscience. Despite an increasing need to analyze and manipulate large networks, only a limited number of tools are available for this task. Here, we describe Stanford Network Analysis Platform (SNAP), a general-purpose, high-performance system that provides easy to use, high-level operations for analysis and manipulation of large networks...
October 2016: ACM Transactions on Intelligent Systems and Technology
https://www.readbyqxmd.com/read/28344774/the-dockstore-enabling-modular-community-focused-sharing-of-docker-based-genomics-tools-and-workflows
#14
Brian D O'Connor, Denis Yuen, Vincent Chung, Andrew G Duncan, Xiang Kun Liu, Janice Patricia, Benedict Paten, Lincoln Stein, Vincent Ferretti
As genomic datasets continue to grow, the feasibility of downloading data to a local organization and running analysis on a traditional compute environment is becoming increasingly problematic. Current large-scale projects, such as the ICGC PanCancer Analysis of Whole Genomes (PCAWG), the Data Platform for the U.S. Precision Medicine Initiative, and the NIH Big Data to Knowledge Center for Translational Genomics, are using cloud-based infrastructure to both host and perform analysis across large data sets. In PCAWG, over 5,800 whole human genomes were aligned and variant called across 14 cloud and HPC environments; the processed data was then made available on the cloud for further analysis and sharing...
2017: F1000Research
https://www.readbyqxmd.com/read/28341160/metabolic-network-failures-in-alzheimer-s-disease-a-biochemical-road%C3%A2-map
#15
Jon B Toledo, Matthias Arnold, Gabi Kastenmüller, Rui Chang, Rebecca A Baillie, Xianlin Han, Madhav Thambisetty, Jessica D Tenenbaum, Karsten Suhre, J Will Thompson, Lisa St John-Williams, Siamak MahmoudianDehkordi, Daniel M Rotroff, John R Jack, Alison Motsinger-Reif, Shannon L Risacher, Colette Blach, Joseph E Lucas, Tyler Massaro, Gregory Louie, Hongjie Zhu, Guido Dallmann, Kristaps Klavins, Therese Koal, Sungeun Kim, Kwangsik Nho, Li Shen, Ramon Casanova, Sudhir Varma, Cristina Legido-Quigley, M Arthur Moseley, Kuixi Zhu, Marc Y R Henrion, Sven J van der Lee, Amy C Harms, Ayse Demirkan, Thomas Hankemeier, Cornelia M van Duijn, John Q Trojanowski, Leslie M Shaw, Andrew J Saykin, Michael W Weiner, P Murali Doraiswamy, Rima Kaddurah-Daouk
INTRODUCTION: The Alzheimer's Disease Research Summits of 2012 and 2015 incorporated experts from academia, industry, and nonprofit organizations to develop new research directions to transform our understanding of Alzheimer's disease (AD) and propel the development of critically needed therapies. In response to their recommendations, big data at multiple levels are being generated and integrated to study network failures in disease. We used metabolomics as a global biochemical approach to identify peripheral metabolic changes in AD patients and correlate them to cerebrospinal fluid pathology markers, imaging features, and cognitive performance...
March 21, 2017: Alzheimer's & Dementia: the Journal of the Alzheimer's Association
https://www.readbyqxmd.com/read/28335044/semi-automated-de-identification-of-german-content-sensitive-reports-for-big-data-analytics
#16
Hannes Seuss, Peter Dankerl, Matthias Ihle, Andrea Grandjean, Rebecca Hammon, Nicola Kaestle, Peter A Fasching, Christian Maier, Jan Christoph, Martin Sedlmayr, Alexander Cavallaro, Matthias Hammon
Purpose Projects involving collaborations between different institutions require data security via selective de-identification of words or phrases. A semi-automated de-identification tool was developed and evaluated on different types of medical reports natively and after adapting the algorithm to the text structure. Materials and Methods A semi-automated de-identification tool was developed and evaluated for its sensitivity and specificity in detecting sensitive content in written reports. Data from 4671 pathology reports (4105 + 566 in two different formats), 2804 medical reports, 1008 operation reports, and 6223 radiology reports of 1167 patients suffering from breast cancer were de-identified...
March 23, 2017: RöFo: Fortschritte Auf Dem Gebiete der Röntgenstrahlen und der Nuklearmedizin
https://www.readbyqxmd.com/read/28333183/machine-learning-algorithms-for-objective-remission-and-clinical-outcomes-with-thiopurines
#17
Akbar K Waljee, Kay Sauder, Anand Patel, Sandeep Segar, Boang Liu, Yiwei Zhang, Ji Zhu, Ryan W Stidham, Ulysses Balis, Peter D R Higgins
Background and Aims: Big data analytics leverage patterns in data to harvest valuable information, but are rarely implemented in clinical care. Optimising thiopurine therapy for inflammatory bowel disease [IBD] has proved difficult. Current methods using 6-thioguanine nucleotide [6-TGN] metabolites have failed in randomized controlled trials [RCTs], and have not been used to predict objective remission [OR]. Our aims were to: 1) develop machine learning algorithms [MLA] using laboratory values and age to identify patients in objective remission on thiopurines; and 2) determine whether achieving algorithm-predicted objective remission resulted in fewer clinical events per year...
March 14, 2017: Journal of Crohn's & Colitis
https://www.readbyqxmd.com/read/28301733/big-data-analytics-in-chemical-engineering
#18
Leo Chiang, Bo Lu, Ivan Castillo
Big data analytics is the journey to turn data into insights for more informed business and operational decisions. As the chemical engineering community is collecting more data (volume) from different sources (variety), this journey becomes more challenging in terms of using the right data and the right tools (analytics) to make the right decisions in real time (velocity). This article highlights recent big data advancements in five industries, including chemicals, energy, semiconductors, pharmaceuticals, and food, and then discusses technical, platform, and culture challenges...
February 27, 2017: Annual Review of Chemical and Biomolecular Engineering
https://www.readbyqxmd.com/read/28282239/the-role-of-teamwork-in-the-analysis-of-big-data-a-study-of-visual-analytics-and-box-office-prediction
#19
Verica Buchanan, Yafeng Lu, Nathan McNeese, Michael Steptoe, Ross Maciejewski, Nancy Cooke
Historically, domains such as business intelligence would require a single analyst to engage with data, develop a model, answer operational questions, and predict future behaviors. However, as the problems and domains become more complex, organizations are employing teams of analysts to explore and model data to generate knowledge. Furthermore, given the rapid increase in data collection, organizations are struggling to develop practices for intelligence analysis in the era of big data. Currently, a variety of machine learning and data mining techniques are available to model data and to generate insights and predictions, and developments in the field of visual analytics have focused on how to effectively link data mining algorithms with interactive visuals to enable analysts to explore, understand, and interact with data and data models...
March 2017: Big Data
https://www.readbyqxmd.com/read/28280932/bits-and-bytes-the-future-of-radiology-lies-in-informatics-and-information-technology
#20
James A Brink, Ronald L Arenson, Thomas M Grist, Jonathan S Lewin, Dieter Enzmann
Advances in informatics and information technology are sure to alter the practice of medical imaging and image-guided therapies substantially over the next decade. Each element of the imaging continuum will be affected by substantial increases in computing capacity coincident with the seamless integration of digital technology into our society at large. This article focuses primarily on areas where this IT transformation is likely to have a profound effect on the practice of radiology. KEY POINTS: • Clinical decision support ensures consistent and appropriate resource utilization...
March 9, 2017: European Radiology
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