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https://www.readbyqxmd.com/read/28925590/analytic-methods-for-evaluating-patterns-of-multiple-congenital-anomalies-in-birth-defect-registries
#1
REVIEW
A J Agopian, Jane A Evans, Philip J Lupo
BACKGROUND: It is estimated that 20 to 30% of infants with birth defects have two or more birth defects. Among these infants with multiple congenital anomalies (MCA), co-occurring anomalies may represent either chance (i.e., unrelated etiologies) or pathogenically associated patterns of anomalies. While some MCA patterns have been recognized and described (e.g., known syndromes), others have not been identified or characterized. Elucidating these patterns may result in a better understanding of the etiologies of these MCAs...
September 19, 2017: Birth defects research
https://www.readbyqxmd.com/read/28924330/manufacturing-data-analytics-using-a-virtual-factory-representation
#2
Sanjay Jain, Guodong Shao, Seung-Jun Shin
Large manufacturers have been using simulation to support decision-making for design and production. However, with the advancement of technologies and the emergence of big data, simulation can be utilised to perform and support data analytics for associated performance gains. This requires not only significant model development expertise, but also huge data collection and analysis efforts. This paper presents an approach within the frameworks of Design Science Research Methodology and prototyping to address the challenge of increasing the use of modelling, simulation and data analytics in manufacturing via reduction of the development effort...
2017: International Journal of Production Economics
https://www.readbyqxmd.com/read/28918390/a-glossary-for-big-data-in-population-and-public-health-discussion-and-commentary-on-terminology-and-research-methods
#3
Daniel Fuller, Richard Buote, Kevin Stanley
The volume and velocity of data are growing rapidly and big data analytics are being applied to these data in many fields. Population and public health researchers may be unfamiliar with the terminology and statistical methods used in big data. This creates a barrier to the application of big data analytics. The purpose of this glossary is to define terms used in big data and big data analytics and to contextualise these terms. We define the five Vs of big data and provide definitions and distinctions for data mining, machine learning and deep learning, among other terms...
September 16, 2017: Journal of Epidemiology and Community Health
https://www.readbyqxmd.com/read/28913177/big-data-in-designing-clinical-trials-opportunities-and-challenges
#4
Charles S Mayo, Martha M Matuszak, Matthew J Schipper, Shruti Jolly, James A Hayman, Randall K Ten Haken
Emergence of big data analytics resource systems (BDARSs) as a part of routine practice in Radiation Oncology is on the horizon. Gradually, individual researchers, vendors, and professional societies are leading initiatives to create and demonstrate use of automated systems. What are the implications for design of clinical trials, as these systems emerge? Gold standard, randomized controlled trials (RCTs) have high internal validity for the patients and settings fitting constraints of the trial, but also have limitations including: reproducibility, generalizability to routine practice, infrequent external validation, selection bias, characterization of confounding factors, ethics, and use for rare events...
2017: Frontiers in Oncology
https://www.readbyqxmd.com/read/28887351/using-predictive-analytics-and-big-data-to-optimize-pharmaceutical-outcomes
#5
Inmaculada Hernandez, Yuting Zhang
PURPOSE: The steps involved, the resources needed, and the challenges associated with applying predictive analytics in healthcare are described, with a review of successful applications of predictive analytics in implementing population health management interventions that target medication-related patient outcomes. SUMMARY: In healthcare, the term big data typically refers to large quantities of electronic health record, administrative claims, and clinical trial data as well as data collected from smartphone applications, wearable devices, social media, and personal genomics services; predictive analytics refers to innovative methods of analysis developed to overcome challenges associated with big data, including a variety of statistical techniques ranging from predictive modeling to machine learning to data mining...
September 15, 2017: American Journal of Health-system Pharmacy: AJHP
https://www.readbyqxmd.com/read/28883909/computing-platforms-for-big-biological-data-analytics-perspectives-and-challenges
#6
REVIEW
Zekun Yin, Haidong Lan, Guangming Tan, Mian Lu, Athanasios V Vasilakos, Weiguo Liu
The last decade has witnessed an explosion in the amount of available biological sequence data, due to the rapid progress of high-throughput sequencing projects. However, the biological data amount is becoming so great that traditional data analysis platforms and methods can no longer meet the need to rapidly perform data analysis tasks in life sciences. As a result, both biologists and computer scientists are facing the challenge of gaining a profound insight into the deepest biological functions from big biological data...
2017: Computational and Structural Biotechnology Journal
https://www.readbyqxmd.com/read/28880882/putting-the-methodological-brakes-on-claims-to-measure-national-happiness-through-twitter-methodological-limitations-in-social-media-analytics
#7
Eric Allen Jensen
With the rapid global proliferation of social media, there has been growing interest in using this existing source of easily accessible 'big data' to develop social science knowledge. However, amidst the big data gold rush, it is important that long-established principles of good social research are not ignored. This article critically evaluates Mitchell et al.'s (2013) study, 'The Geography of Happiness: Connecting Twitter Sentiment and Expression, Demographics, and Objective Characteristics of Place', demonstrating the importance of attending to key methodological issues associated with secondary data analysis...
2017: PloS One
https://www.readbyqxmd.com/read/28880227/providing-personalized-energy-management-and-awareness-services-for-energy-efficiency-in-smart-buildings
#8
Eleni Fotopoulou, Anastasios Zafeiropoulos, Fernando Terroso-Sáenz, Umutcan Şimşek, Aurora González-Vidal, George Tsiolis, Panagiotis Gouvas, Paris Liapis, Anna Fensel, Antonio Skarmeta
Considering that the largest part of end-use energy consumption worldwide is associated with the buildings sector, there is an inherent need for the conceptualization, specification, implementation, and instantiation of novel solutions in smart buildings, able to achieve significant reductions in energy consumption through the adoption of energy efficient techniques and the active engagement of the occupants. Towards the design of such solutions, the identification of the main energy consuming factors, trends, and patterns, along with the appropriate modeling and understanding of the occupants' behavior and the potential for the adoption of environmentally-friendly lifestyle changes have to be realized...
September 7, 2017: Sensors
https://www.readbyqxmd.com/read/28870383/advancing-alzheimer-s-research-a-review-of-big-data-promises
#9
REVIEW
Rui Zhang, Gyorgy Simon, Fang Yu
OBJECTIVE: To review the current state of science using big data to advance Alzheimer's disease (AD) research and practice. In particular, we analyzed the types of research foci addressed, corresponding methods employed and study findings reported using big data in AD. METHOD: Systematic review was conducted for articles published in PubMed from January 1, 2010 through December 31, 2015. Keywords with AD and big data analytics were used for literature retrieval...
October 2017: International Journal of Medical Informatics
https://www.readbyqxmd.com/read/28866555/visualizing-big-data-outliers-through-distributed-aggregation
#10
Leland Wilkinson
Visualizing outliers in massive datasets requires statistical pre-processing in order to reduce the scale of the problem to a size amenable to rendering systems like D3, Plotly or analytic systems like R or SAS. This paper presents a new algorithm, called hdoutliers, for detecting multidimensional outliers. It is unique for a) dealing with a mixture of categorical and continuous variables, b) dealing with big-p (many columns of data), c) dealing with big-n (many rows of data), d) dealing with outliers that mask other outliers, and e) dealing consistently with unidimensional and multidimensional datasets...
August 29, 2017: IEEE Transactions on Visualization and Computer Graphics
https://www.readbyqxmd.com/read/28864810/research-and-discovery-science-and-the-future-of-dental-education-and-practice
#11
Peter J Polverini, Paul H Krebsbach
Dental graduates of 2040 will face new and complex challenges. If they are to meet these challenges, dental schools must develop a research and discovery mission that will equip graduates with the new knowledge required to function in a modern health care environment. The dental practitioner of 2040 will place greater emphasis on risk assessment, disease prevention, and health maintenance; and the emerging discipline of precision medicine and systems biology will revolutionize disease diagnosis and reveal new targeted therapies...
September 2017: Journal of Dental Education
https://www.readbyqxmd.com/read/28846162/wound-healing-outcomes-using-big-data-and-a-modified-intent-to-treat-method-as-a-metric-for-reporting-healing-rates
#12
William J Ennis, Rachel A Hoffman, Geoffrey C Gurtner, Robert S Kirsner, Hanna M Gordon
INTRODUCTION: Chronic wounds are increasing in prevalence and are a costly problem for the US healthcare system and throughout the world. Typically outcomes studies in the field of wound care have been limited to small clinical trials, comparative effectiveness cohorts and attempts to extrapolate results from claims data-bases. As a result, outcomes in real world clinical settings may differ from these published studies. OBJECTIVES: This study presents a modified intent-to-treat framework for measuring wound outcomes and measures the consistency of population based outcomes across two distinct settings...
August 28, 2017: Wound Repair and Regeneration
https://www.readbyqxmd.com/read/28818819/quantifying-human-movement-using-the-movn-smartphone-app-validation-and-field-study
#13
Ralph Maddison, Luke Gemming, Javier Monedero, Linda Bolger, Sarahjane Belton, Johann Issartel, Samantha Marsh, Artur Direito, Madeleine Solenhill, Jinfeng Zhao, Daniel John Exeter, Harshvardhan Vathsangam, Jonathan Charles Rawstorn
BACKGROUND: The use of embedded smartphone sensors offers opportunities to measure physical activity (PA) and human movement. Big data-which includes billions of digital traces-offers scientists a new lens to examine PA in fine-grained detail and allows us to track people's geocoded movement patterns to determine their interaction with the environment. OBJECTIVE: The objective of this study was to examine the validity of the Movn smartphone app (Moving Analytics) for collecting PA and human movement data...
August 17, 2017: JMIR MHealth and UHealth
https://www.readbyqxmd.com/read/28816500/research-challenges-in-financial-data-modeling-and-analysis
#14
Lewis Alexander, Sanjiv R Das, Zachary Ives, H V Jagadish, Claire Monteleoni
Significant research challenges must be addressed in the cleaning, transformation, integration, modeling, and analytics of Big Data sources for finance. This article surveys the progress made so far in this direction and obstacles yet to be overcome. These are issues that are of interest to data-driven financial institutions in both corporate finance and consumer finance. These challenges are also of interest to the legal profession as well as to regulators. The discussion is relevant to technology firms that support the growing field of FinTech...
August 17, 2017: Big Data
https://www.readbyqxmd.com/read/28808136/eplant-visualizing-and-exploring-multiple-levels-of-data-for-hypothesis-generation-in-plant-biology
#15
Jamie Waese, Jim Fan, Asher Pasha, Hans Yu, Geoffrey Fucile, Ruian Shi, Matthew Cumming, Lawrence Kelley, Michael Sternberg, Vivek Krishnakumar, Erik Ferlanti, Jason Miller, Chris Town, Wolfgang Stuerzlinger, Nicholas J Provart
A big challenge in current systems biology research arises when different types of data must be accessed from separate sources and visualized using separate tools. The high cognitive load required to navigate such a workflow is detrimental to hypothesis generation. Accordingly, there is a need for a robust research platform that incorporates all data, and provides integrated search, analysis, and visualization features through a single portal. Here, we present ePlant (http://bar.utoronto.ca/eplant), a visual analytic tool for exploring multiple levels of Arabidopsis data through a zoomable user interface...
August 14, 2017: Plant Cell
https://www.readbyqxmd.com/read/28806228/legal-and-ethical-concerns-of-big-data-predictive-analytics
#16
Shirley S Paulson, Elizabeth Scruth
No abstract text is available yet for this article.
September 2017: Clinical Nurse Specialist CNS
https://www.readbyqxmd.com/read/28802713/detecting-exact-breakpoints-of-deletions-with-diversity-in-hepatitis-b-viral-genomic-dna-from-next-generation-sequencing-data
#17
Ji-Hong Cheng, Wen-Chun Liu, Ting-Tsung Chang, Sun-Yuan Hsieh, Vincent S Tseng
Many studies have suggested that deletions of Hepatitis B Viral (HBV) are associated with the development of progressive liver diseases, even ultimately resulting in hepatocellular carcinoma (HCC). Among the methods for detecting deletions from next-generation sequencing (NGS) data, few methods considered the characteristics of virus, such as high evolution rates and high divergence among the different HBV genomes. Sequencing high divergence HBV genome sequences using the NGS technology outputs millions of reads...
August 9, 2017: Methods: a Companion to Methods in Enzymology
https://www.readbyqxmd.com/read/28783079/an-ultra-low-power-turning-angle-based-biomedical-signal-compression-engine-with-adaptive-threshold-tuning
#18
Jun Zhou, Chao Wang
Intelligent sensing is drastically changing our everyday life including healthcare by biomedical signal monitoring, collection, and analytics. However, long-term healthcare monitoring generates tremendous data volume and demands significant wireless transmission power, which imposes a big challenge for wearable healthcare sensors usually powered by batteries. Efficient compression engine design to reduce wireless transmission data rate with ultra-low power consumption is essential for wearable miniaturized healthcare sensor systems...
August 6, 2017: Sensors
https://www.readbyqxmd.com/read/28782717/in-silico-approaches-for-unveiling-novel-glycobiomarkers-in-cancer
#19
Rita Azevedo, André M N Silva, Celso A Reis, Lúcio Lara Santos, José Alexandre Ferreira
Glycosylation is one of the most common and dynamic post-translational modification of cell surface and secreted proteins. Cancer cells display unique glycosylation patterns that decisively contribute to drive oncogenic behavior, including disease progression and dissemination. Moreover, alterations in glycosylation are often responsible for the creation of protein signatures holding significant biomarker value and potential for targeted therapeutics. Accordingly, many analytical protocols have been outlined for the identification of abnormally glycosylated proteins by mass spectrometry...
August 4, 2017: Journal of Proteomics
https://www.readbyqxmd.com/read/28771321/activity-based-detection-of-consumption-of-synthetic-cannabinoids-in-authentic-urine-samples-using-a-stable-cannabinoid-reporter-system
#20
Annelies Cannaert, Florian Franz, Volker Auwärter, Christophe P Stove
Synthetic cannabinoids (SCs) continue to be the largest group of new psychoactive substances (NPS) monitored by the European Monitoring Center of Drugs and Drugs of Abuse (EMCDDA). The identification and subsequent prohibition of single SCs has driven clandestine chemists to produce analogues of increasing structural diversity, intended to evade legislation. That structural diversity, combined with the mostly unknown metabolic profiles of these new SCs, poses a big challenge for the conventional targeted analytical assays, as it is difficult to screen for "unknown" compounds...
September 5, 2017: Analytical Chemistry
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