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"Big data"

Piotr Klukowski, Michal Augoff, Maciej Zieba, Maciej Drwal, Adam Gonczarek, Michal J Walczak
Motivation: Automated selection of signals in protein NMR spectra, known as peak picking, has been studied for over 20 years, nevertheless existing peak picking methods are still largely deficient. Accurate and precise automated peak picking would accelerate the structure calculation, and analysis of dynamics and interactions of macromolecules. Recent advancement in handling big data, together with an outburst of machine learning techniques, offer an opportunity to tackle the peak picking problem substantially faster than manual picking and on par with human accuracy...
March 14, 2018: Bioinformatics
Iwao Sugitani, Naoyoshi Onoda, Ken-Ichi Ito, Shinichi Suzuki
Anaplastic thyroid carcinoma (ATC) accounts for only 1 to 2% of all thyroid carcinomas, but it is one of the most lethal neoplasms in humans. To obtain further insights into this "orphan disease," we have established the ATC Research Consortium of Japan (ATCCJ) in 2009. It represents a multicenter registry for ATC that have been treated in Japan. To date, 67 institutions have taken part in the collaborative research system and over 1,200 cases have been accumulated in its database. Using this big data, several retrospective studies were carried out to evaluate 1) prognostic factors to determine initial treatment policy, 2) significance of extended radical surgery for Stage IVB cases, 3) characteristics of ATC incidentally found on pathological examination and 4) pathological features of ATC with long-term survival...
2018: Journal of Nippon Medical School, Nippon Ika Daigaku Zasshi
Richard H Savel, Ariel L Shiloh, Ronald J Simon, Yizhak Kupfer
No abstract text is available yet for this article.
April 2018: Critical Care Medicine
Saad Chahine, Kulamakan Mahan Kulasegaram, Sarah Wright, Sandra Monteiro, Lawrence E M Grierson, Cassandra Barber, Stefanie S Sebok-Syer, Meghan McConnell, Wendy Yen, Andre De Champlain, Claire Touchie
There exists an assumption that improving medical education will improve patient care. While seemingly logical, this premise has rarely been investigated. In this Invited Commentary, the authors propose the use of big data to test this assumption. The authors present a few example research studies linking education and patient care outcomes and argue that using big data may more easily facilitate the process needed to investigate this assumption. The authors also propose that collaboration is needed to link educational and health care data...
March 13, 2018: Academic Medicine: Journal of the Association of American Medical Colleges
Vineet M Arora
With the advent of electronic medical records (EMRs) fueling the rise of big data, the use of predictive analytics, machine learning, and artificial intelligence are touted as transformational tools to improve clinical care. While major investments are being made in using big data to transform health care delivery, little effort has been directed toward exploiting big data to improve graduate medical education (GME). Because our current system relies on faculty observations of competence, it is not unreasonable to ask whether big data in the form of clinical EMRs and other novel data sources can answer questions of importance in GME such as when is a resident ready for independent practice...
March 13, 2018: Academic Medicine: Journal of the Association of American Medical Colleges
J Ngai, M Adil
No abstract text is available yet for this article.
December 2017: Journal of the Royal College of Physicians of Edinburgh
Goutham Rao, Paul Epner, Victoria Bauer, Anthony Solomonides, David E Newman-Toker
Diagnostic error is a serious public health problem to which knowledge gaps and associated cognitive error contribute significantly. Identifying diagnostic approaches to common problems in ambulatory care associated with more timely and accurate diagnosis and lower cost and harm associated with diagnostic evaluation is an important priority for health care systems, clinicians, and of course patients. Unfortunately, guidance on how best to approach diagnosis in patients with common presenting complaints such as abdominal pain, dizziness, and fatigue is lacking...
June 27, 2017: Diagnosis
Xiajing Gong, Meng Hu, Liang Zhao
Additional value can be potentially created by applying big data tools to address pharmacometric problems. The performances of machine learning (ML) methods and the Cox regression model were evaluated based on simulated time-to-event data synthesized under various preset scenarios, i.e., with linear vs. nonlinear and dependent vs. independent predictors in the proportional hazard function, or with high-dimensional data featured by a large number of predictor variables. Our results showed that ML-based methods outperformed the Cox model in prediction performance as assessed by concordance index and in identifying the preset influential variables for high-dimensional data...
March 13, 2018: Clinical and Translational Science
Xiang-Tian Yu, Tao Zeng
The diversity and huge omics data take biology and biomedicine research and application into a big data era, just like that popular in human society a decade ago. They are opening a new challenge from horizontal data ensemble (e.g., the similar types of data collected from different labs or companies) to vertical data ensemble (e.g., the different types of data collected for a group of person with match information), which requires the integrative analysis in biology and biomedicine and also asks for emergent development of data integration to address the great changes from previous population-guided to newly individual-guided investigations...
2018: Methods in Molecular Biology
K J Billingsley, S Bandres-Ciga, S Saez-Atienzar, A B Singleton
Over the last two decades, we have witnessed a revolution in the field of Parkinson's disease (PD) genetics. Great advances have been made in identifying many loci that confer a risk for PD, which has subsequently led to an improved understanding of the molecular pathways involved in disease pathogenesis. Despite this success, it is predicted that only a relatively small proportion of the phenotypic variability has been explained by genetics. Therefore, it is clear that common heritable components of disease are still to be identified...
March 13, 2018: Cell and Tissue Research
K B Greenland, M G Irwin
No abstract text is available yet for this article.
March 13, 2018: Anaesthesia
Andrew L Beam, Isaac S Kohane
No abstract text is available yet for this article.
March 12, 2018: JAMA: the Journal of the American Medical Association
Amaryllis Mavragani, Alexia Sampri, Karla Sypsa, Konstantinos P Tsagarakis
BACKGROUND: With the internet's penetration and use constantly expanding, this vast amount of information can be employed in order to better assess issues in the US health care system. Google Trends, a popular tool in big data analytics, has been widely used in the past to examine interest in various medical and health-related topics and has shown great potential in forecastings, predictions, and nowcastings. As empirical relationships between online queries and human behavior have been shown to exist, a new opportunity to explore the behavior toward asthma-a common respiratory disease-is present...
March 12, 2018: JMIR Public Health and Surveillance
Agnes Norbury, Ben Seymour
Response rates to available treatments for psychological and chronic pain disorders are poor, and there is a considerable burden of suffering and disability for patients, who often cycle through several rounds of ineffective treatment. As individuals presenting to the clinic with symptoms of these disorders are likely to be heterogeneous, there is considerable interest in the possibility that different constellations of signs could be used to identify subgroups of patients that might preferentially benefit from particular kinds of treatment...
2018: F1000Research
Chayakrit Krittanawong
No abstract text is available yet for this article.
February 23, 2018: International Journal of Cardiology
Nathan Scudder, Dennis McNevin, Sally F Kelty, Simon J Walsh, James Robertson
Use of DNA in forensic science will be significantly influenced by new technology in coming years. Massively parallel sequencing and forensic genomics will hasten the broadening of forensic DNA analysis beyond short tandem repeats for identity towards a wider array of genetic markers, in applications as diverse as predictive phenotyping, ancestry assignment, and full mitochondrial genome analysis. With these new applications come a range of legal and policy implications, as forensic science touches on areas as diverse as 'big data', privacy and protected health information...
March 2018: Science & Justice: Journal of the Forensic Science Society
Nilanjan Dey, Amira S Ashour, Fuqian Shi, Simon James Fong, João Manuel R S Tavares
Medical cyber-physical systems (MCPS) are healthcare critical integration of a network of medical devices. These systems are progressively used in hospitals to achieve a continuous high-quality healthcare. The MCPS design faces numerous challenges, including inoperability, security/privacy, and high assurance in the system software. In the current work, the infrastructure of the cyber-physical systems (CPS) are reviewed and discussed. This article enriched the researches of the networked Medical Device (MD) systems to increase the efficiency and safety of the healthcare...
March 10, 2018: Journal of Medical Systems
Ingunn Björnsdottir, Guri Birgitte Verne
BACKGROUND: Data from large electronic databases are increasingly used in epidemiological research, but golden standards for database validation remain elusive. The Prescription Registry (IPR) and the National Health Service (NHS) databases in Iceland have not undergone formal validation, and gross errors have repeatedly been found in Icelandic statistics on pharmaceuticals. In 2015, new amphetamine tablets entered the Icelandic market, but were withdrawn half a year later due to being substandard...
February 27, 2018: Research in Social & Administrative Pharmacy: RSAP
Xue Yang, Luliang Tang, Xia Zhang, Qingquan Li
Given the popularization of GPS technologies, the massive amount of spatiotemporal GPS traces collected by vehicles are becoming a new kind of big data source for urban geographic information extraction. The growing volume of the dataset, however, creates processing and management difficulties, while the low quality generates uncertainties when investigating human activities. Based on the conception of the error distribution law and position accuracy of the GPS data, we propose in this paper a data cleaning method for this kind of spatial big data using movement consistency...
March 9, 2018: Sensors
Anna Middleton
Genomic data offers a goldmine of information for understanding the contribution genetic variation makes to health and disease. The potential of genomic medicine, to predict, diagnose, manage and treat genetic disease, is underpinned by accurate variant interpretation. This in itself hinges on the ability to access large and varied genomic databases. There is now recognition that international collaboration between research and healthcare systems are paramount to delivering the scale of genomic data required...
March 7, 2018: Human Molecular Genetics
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