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https://www.readbyqxmd.com/read/28445550/classifying-patents-based-on-their-semantic-content
#1
Antonin Bergeaud, Yoann Potiron, Juste Raimbault
In this paper, we extend some usual techniques of classification resulting from a large-scale data-mining and network approach. This new technology, which in particular is designed to be suitable to big data, is used to construct an open consolidated database from raw data on 4 million patents taken from the US patent office from 1976 onward. To build the pattern network, not only do we look at each patent title, but we also examine their full abstract and extract the relevant keywords accordingly. We refer to this classification as semantic approach in contrast with the more common technological approach which consists in taking the topology when considering US Patent office technological classes...
2017: PloS One
https://www.readbyqxmd.com/read/28439835/the-uea-small-rna-workbench-a-suite-of-computational-tools-for-small-rna-analysis
#2
Irina Mohorianu, Matthew Benedict Stocks, Christopher Steven Applegate, Leighton Folkes, Vincent Moulton
RNA silencing (RNA interference, RNAi) is a complex, highly conserved mechanism mediated by short, typically 20-24 nt in length, noncoding RNAs known as small RNAs (sRNAs). They act as guides for the sequence-specific transcriptional and posttranscriptional regulation of target mRNAs and play a key role in the fine-tuning of biological processes such as growth, response to stresses, or defense mechanism.High-throughput sequencing (HTS) technologies are employed to capture the expression levels of sRNA populations...
2017: Methods in Molecular Biology
https://www.readbyqxmd.com/read/28439180/enhancing-diversity-in-biomedical-data-science
#3
Judith E Canner, Archana J McEligot, María-Eglée Pérez, Lei Qian, Xinzhi Zhang
The gap in educational attainment separating underrepresented minorities from Whites and Asians remains wide. Such a gap has significant impact on workforce diversity and inclusion among cross-cutting Biomedical Data Science (BDS) research, which presents great opportunities as well as major challenges for addressing health disparities. This article provides a brief description of the newly established National Institutes of Health Big Data to Knowledge (BD2K) diversity initiatives at four universities: California State University, Monterey Bay; Fisk University; University of Puerto Rico, Río Piedras Campus; and California State University, Fullerton...
2017: Ethnicity & Disease
https://www.readbyqxmd.com/read/28439179/big-data-science-opportunities-and-challenges-to-address-minority-health-and-health-disparities-in-the-21st-century
#4
Xinzhi Zhang, Eliseo J Pérez-Stable, Philip E Bourne, Emmanuel Peprah, O Kenrik Duru, Nancy Breen, David Berrigan, Fred Wood, James S Jackson, David W S Wong, Joshua Denny
Addressing minority health and health disparities has been a missing piece of the puzzle in Big Data science. This article focuses on three priority opportunities that Big Data science may offer to the reduction of health and health care disparities. One opportunity is to incorporate standardized information on demographic and social determinants in electronic health records in order to target ways to improve quality of care for the most disadvantaged populations over time. A second opportunity is to enhance public health surveillance by linking geographical variables and social determinants of health for geographically defined populations to clinical data and health outcomes...
2017: Ethnicity & Disease
https://www.readbyqxmd.com/read/28439178/hispanic-residential-isolation-adhd-diagnosis-and-stimulant-treatment-among-medicaid-insured-youth
#5
Dinci Pennap, Mehmet Burcu, Daniel J Safer, Julie M Zito
OBJECTIVE: This study aimed to evaluate a conceptual framework that assessed the effect of Hispanic residential isolation on Attention Deficit Hyperactivity Disorder (ADHD) health service utilization among 2.2 million publicly insured youth. DESIGN: Cross-sectional. SETTING: Medicaid administrative claims data for ambulatory care services from a US Pacific state linked with US census data. PARTICIPANTS: Youth, aged 2-17 years, continuously enrolled in 2009...
2017: Ethnicity & Disease
https://www.readbyqxmd.com/read/28439176/commentary-in-the-rising-era-of-big-data-small-steps-are-key
#6
EDITORIAL
Nina Heller, Jonathan H Seltzer
Big Data may be useful to identify and perhaps ameliorate health disparities. However, over reliance on the power on Big Data can potentially cause harm. When assessing health disparities, the use of Big Data should be limited to hypothesis generation.
2017: Ethnicity & Disease
https://www.readbyqxmd.com/read/28439175/foreword-big-data-and-its-application-in-health-disparities-research
#7
EDITORIAL
Eberechukwu Onukwugha, O Kenrik Duru, Emmanuel Peprah
The articles presented in this special issue advance the conversation by describing the current efforts, findings and concerns related to Big Data and health disparities. They offer important recommendations and perspectives to consider when designing systems that can usefully leverage Big Data to reduce health disparities. We hope that ongoing Big Data efforts can build on these contributions to advance the conversation, address our embedded assumptions, and identify levers for action to reduce health care disparities...
2017: Ethnicity & Disease
https://www.readbyqxmd.com/read/28437522/statistical-caution-in-big-data-approaches-to-transfusion-medicine-research
#8
Nareg Roubinian, Donald Brambilla, Edward L Murphy
No abstract text is available yet for this article.
April 24, 2017: JAMA Internal Medicine
https://www.readbyqxmd.com/read/28436893/a-parallel-multiclassification-algorithm-for-big-data-using-an-extreme-learning-machine
#9
Mingxing Duan, Kenli Li, Xiangke Liao, Keqin Li
As data sets become larger and more complicated, an extreme learning machine (ELM) that runs in a traditional serial environment cannot realize its ability to be fast and effective. Although a parallel ELM (PELM) based on MapReduce to process large-scale data shows more efficient learning speed than identical ELM algorithms in a serial environment, some operations, such as intermediate results stored on disks and multiple copies for each task, are indispensable, and these operations create a large amount of extra overhead and degrade the learning speed and efficiency of the PELMs...
April 24, 2017: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/28435184/mining-electronic-health-records-data-domestic-violence-and-adverse-health-effects
#10
Gunnur Karakurt, Vishal Patel, Kathleen Whiting, Mehmet Koyutürk
Intimate partner violence (IPV) often culminates in acute physical injury, sexual assault, and mental health issues. It is crucial to understand the healthcare habits of victims to develop interventions that can drastically improve a victim's quality of life and prevent future abuse. The objective of this study is to mine de-identified and aggregated Electronic Health Record data to identify women's health issues that are potentially associated with IPV. In this study we compared health issues of female domestic abuse victims to female non-domestic abuse victims...
January 2017: Journal of Family Violence
https://www.readbyqxmd.com/read/28434559/what-do-george-clooney-and-sarah-jessica-parker-have-in-common-big-data
#11
Toshimasa J Clark, Rebecca J Mieloszyk, Puneet Bhargava
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May 2017: Current Problems in Diagnostic Radiology
https://www.readbyqxmd.com/read/28430088/informatics-for-health-2017-advancing-both-science-and-practice
#12
Philip J Scott, Ronald Cornet, Colin McCowan, Niels Peek, Paolo Fraccaro, Nophar Geifman, Wouter T Gude, William Hulme, Glen P Martin, Richard Williams
INTRODUCTION: The Informatics for Health congress, 24-26 April 2017, in Manchester, UK, brought together the Medical Informatics Europe (MIE) conference and the Farr Institute International Conference. This special issue of the Journal of Innovation in Health Informatics contains 113 presentation abstracts and 149 poster abstracts from the congress. DISCUSSION: The twin programmes of "Big Data" and "Digital Health" are not always joined up by coherent policy and investment priorities...
April 21, 2017: Journal of Innovation in Health Informatics
https://www.readbyqxmd.com/read/28429498/separate-neural-systems-for-behavioral-change-and-for-emotional-responses-to-failure-during-behavioral-inhibition
#13
Wanlu Deng, Edmund T Rolls, Xiaoxi Ji, Trevor W Robbins, Tobias Banaschewski, Arun L W Bokde, Uli Bromberg, Christian Buechel, Sylvane Desrivières, Patricia Conrod, Herta Flor, Vincent Frouin, Juergen Gallinat, Hugh Garavan, Penny Gowland, Andreas Heinz, Bernd Ittermann, Jean-Luc Martinot, Herve Lemaitre, Frauke Nees, Dimitri Papadopoulos Orfanos, Luise Poustka, Michael N Smolka, Henrik Walter, Robert Whelan, Gunter Schumann, Jianfeng Feng
To analyze the involvement of different brain regions in behavioral inhibition and impulsiveness, differences in activation were investigated in fMRI data from a response inhibition task, the stop-signal task, in 1709 participants. First, areas activated more in stop-success (SS) than stop-failure (SF) included the lateral orbitofrontal cortex (OFC) extending into the inferior frontal gyrus (ventrolateral prefrontal cortex, BA 47/12), and the dorsolateral prefrontal cortex (DLPFC). Second, the anterior cingulate and anterior insula (AI) were activated more on failure trials, specifically in SF versus SS...
April 21, 2017: Human Brain Mapping
https://www.readbyqxmd.com/read/28427464/accuracy-of-low-density-lipoprotein-cholesterol-estimation-at-very-low-levels
#14
Renato Quispe, Aditya Hendrani, Mohamed B Elshazly, Erin D Michos, John W McEvoy, Michael J Blaha, Maciej Banach, Krishnaji R Kulkarni, Peter P Toth, Josef Coresh, Roger S Blumenthal, Steven R Jones, Seth S Martin
BACKGROUND: As the approach to low-density lipoprotein cholesterol (LDL-C) lowering becomes increasingly intensive, accurate assessment of LDL-C at very low levels warrants closer attention in individualized clinical efficacy and safety evaluation. We aimed to assess the accuracy of LDL-C estimation at very low levels by the Friedewald equation, the de facto clinical standard, and compare its accuracy with a novel, big data-derived LDL-C estimate. METHODS: In 191,333 individuals with Friedewald LDL-C < 70 mg/dL, we compared the accuracy of Friedewald and novel LDL-C values in relation to direct measurements by Vertical Auto Profile ultracentrifugation...
April 20, 2017: BMC Medicine
https://www.readbyqxmd.com/read/28426908/clinically-useful-brain-imaging-for-neuropsychiatry-how-can-we-get-there
#15
REVIEW
Michael P Milham, R Cameron Craddock, Arno Klein
Despite decades of research, visions of transforming neuropsychiatry through the development of brain imaging-based "growth charts" or "lab tests" have remained out of reach. In recent years, there is renewed enthusiasm about the prospect of achieving clinically useful tools capable of aiding the diagnosis and management of neuropsychiatric disorders. The present work explores the basis for this enthusiasm. We assert that there is no single advance that currently has the potential to drive the field of clinical brain imaging forward...
April 20, 2017: Depression and Anxiety
https://www.readbyqxmd.com/read/28425058/finding-the-traces-of-behavioral-and-cognitive-processes-in-big-data-and-naturally-occurring-datasets
#16
Alexandra Paxton, Thomas L Griffiths
Today, people generate and store more data than ever before as they interact with both real and virtual environments. These digital traces of behavior and cognition offer cognitive scientists and psychologists an unprecedented opportunity to test theories outside the laboratory. Despite general excitement about big data and naturally occurring datasets among researchers, three "gaps" stand in the way of their wider adoption in theory-driven research: the imagination gap, the skills gap, and the culture gap...
April 19, 2017: Behavior Research Methods
https://www.readbyqxmd.com/read/28423778/developing-healthcare-data-analytics-apps-with-open-data-science-tools
#17
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/28423489/target-of-obstructive-sleep-apnea-syndrome-merge-lung-cancer-based-on-big-data-platform
#18
Lifeng Li, Jingli Lu, Wenhua Xue, Liping Wang, Yunkai Zhai, Zhirui Fan, Ge Wu, Feifei Fan, Jieyao Li, Chaoqi Zhang, Yi Zhang, Jie Zhao
Based on our hospital database, the incidence of lung cancer diagnoses was similar in obstructive sleep apnea Syndrome (OSAS) and hospital general population; among individual with a diagnosis of lung cancer, the presence of OSAS was associated with an increased risk for mortality. In the gene expression and network-level information, we revealed significant alterations of molecules related to HIF1 and metabolic pathways in the hypoxic-conditioned lung cancer cells. We also observed that GBE1 and HK2 are downstream of HIF1 pathway important in hypoxia-conditioned lung cancer cell...
March 28, 2017: Oncotarget
https://www.readbyqxmd.com/read/28422856/a-cross-sectional-evaluation-of-meditation-experience-on-electroencephalography-data-by-artificial-neural-network-and-support-vector-machine-classifiers
#19
Yu-Hao Lee, Ya-Ju Hsieh, Yung-Jong Shiah, Yu-Huei Lin, Chiao-Yun Chen, Yu-Chang Tyan, JiaCheng GengQiu, Chung-Yao Hsu, Sharon Chia-Ju Chen
To quantitate the meditation experience is a subjective and complex issue because it is confounded by many factors such as emotional state, method of meditation, and personal physical condition. In this study, we propose a strategy with a cross-sectional analysis to evaluate the meditation experience with 2 artificial intelligence techniques: artificial neural network and support vector machine. Within this analysis system, 3 features of the electroencephalography alpha spectrum and variant normalizing scaling are manipulated as the evaluating variables for the detection of accuracy...
April 2017: Medicine (Baltimore)
https://www.readbyqxmd.com/read/28418450/the-draw-backs-of-big-data
#20
John A Gonzales, Thomas M Lietman, Nisha R Acharya
No abstract text is available yet for this article.
April 13, 2017: JAMA Ophthalmology
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