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The Foundation of Precision Medicine: Integration of Electronic Health Records with Nenomics Through Basic, Clinical, and Translational Research

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Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889198726 Year: Pages: 194 DOI: 10.3389/978-2-88919-872-6 Language: English
Publisher: Frontiers Media SA
Subject: Genetics --- Science (General)
Added to DOAB on : 2016-01-19 14:05:46
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This eBook contains the 19 articles that were part of a Special Topic in Frontiers in Genetics entitled “Genetics Research in Electronic Health Records Linked to DNA Biobanks”. The Special Issue was published on-line in 2014-2015 and contained papers representing the diverse research ongoing in the integration of electronic health records (EHR) with genomics through basic, clinical, and translational research. We have divided the eBook into four Chapters. Chapter 1 describes the Electronic Medical Records and Genomics (eMERGE) network and its contri-bution to genomics. It highlights methodological questions related to large data sets such as imputation and population stratification. Chapter 2 describes the results of genetic studies on different diseases for which all the phenotypic information was extracted from the EHR with highly specific ePhenotyping algorithms. Chapter 3 focuses on more complex analyses of the genome including copy number variants (CNV), pleiotropy com-bined with phenome-wide association studies (PheWAS), and epistasis (gene-gene interactions). Chapter 4 discusses the use of genetic data together with EHR-derived clinical data in clinical settings, and how to return genetic results to patients and providers. It also contains a comprehensive review on genetic risk scores. We have included mostly Original Research Articles in the eBook, but also Reviews and Methods papers on the relevant topics of analyzing and integrating genomic data. The release of this eBook is timely, since several countries are launching Precision Medicine initiatives. Precision Medicine is a new concept in patient care taking into account individual variability in genetic, environmental and lifestyle factors, when treating diseases or trying to prevent them from developing. It has become an important focus for biomedical, clinical and translational informatics. The papers presented in this eBook are well positioned to educate the readers about Precision Medicine and to demonstrate the potential study designs, methods, strategies, and applications where this type of research can be performed successfully. The ultimate goal is to improve diagnostics and provide better, more targeted care to the patient.

Overcoming Data Scarcity in Earth Science

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ISBN: 9783039282104 / 9783039282111 Year: Pages: 94 DOI: 10.3390/books978-3-03928-211-1 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering --- Environmental Engineering
Added to DOAB on : 2020-06-09 16:38:57
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heavily Environmental mathematical models represent one of the key aids for scientists to forecast, create, and evaluate complex scenarios. These models rely on the data collected by direct field observations. However, assembly of a functional and comprehensive dataset for any environmental variable is difficult, mainly because of i) the high cost of the monitoring campaigns and ii) the low reliability of measurements (e.g., due to occurrences of equipment malfunctions and/or issues related to equipment location). The lack of a sufficient amount of Earth science data may induce an inadequate representation of the response’s complexity in any environmental system to any type of input/change, both natural and human-induced. In such a case, before undertaking expensive studies to gather and analyze additional data, it is reasonable to first understand what enhancement in estimates of system performance would result if all the available data could be well exploited. Missing data imputation is an important task in cases where it is crucial to use all available data and not discard records with missing values. Different approaches are available to deal with missing data. Traditional statistical data completion methods are used in different domains to deal with single and multiple imputation problems. More recently, machine learning techniques, such as clustering and classification, have been proposed to complete missing data. This book showcases the body of knowledge that is aimed at improving the capacity to exploit the available data to better represent, understand, predict, and manage the behavior of environmental systems at all practical scales.

Human Mobility, Spatiotemporal Context, and Environmental Health: Recent Advances in Approaches and Methods

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ISBN: 9783039211838 9783039211845 Year: Pages: 382 DOI: 10.3390/books978-3-03921-184-5 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Medicine (General)
Added to DOAB on : 2019-08-28 11:21:27
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Environmental health researchers have long used concepts like the neighborhood effect to assessing people’s exposure to environmental influences and the associated health impact. However, these are static notions that ignore people’s daily mobility at various spatial and temporal scales (e.g., daily travel, migratory movements, and movements over the life course) and the influence of neighborhood contexts outside their residential neighborhoods. Recent studies have started to incorporate human mobility, non-residential neighborhoods, and the temporality of exposures through collecting and using data from GPS, accelerometers, mobile phones, various types of sensors, and social media. Innovative approaches and methods have been developed. This Special Issue aims to showcase studies that use new approaches, methods, and data to examine the role of human mobility and non-residential contexts on human health behaviors and outcomes. It includes 21 articles that cover a wide range of topics, including individual exposure to air pollution, exposure and access to green spaces, spatial access to healthcare services, environmental influences on physical activity, food environmental and diet behavior, exposure to noise and its impact on mental health, and broader methodological issues such as the uncertain geographic context problem (UGCoP) and the neighborhood effect averaging problem (NEAP). This collection will be a valuable reference for scholars and students interested in recent advances in the concepts and methods in environmental health and health geography.

Keywords

obesity --- built environment --- activity space --- regression analysis --- UGCoP --- foodscape exposure --- activity space --- commuting route --- space-time kernel density estimation --- time-weighted exposure --- Beijing --- cycling for transportation --- bike paths --- train stations --- subway stations --- adults --- Brazil --- fuel consumption --- emissions estimation --- GPS trace --- big data --- air pollution exposure --- human mobility --- mobile phone data --- dynamic assessment --- GIS --- GPS --- activity space --- environmental exposure --- the uncertain geographic context problem --- noise pollution --- mental disorders --- built environment --- multilevel model --- China --- PM concentrations --- crop residue burning --- correlation analysis --- interannual and seasonal variations --- China --- the neighborhood effect averaging problem (NEAP) --- human mobility --- environmental exposure --- the uncertain geographic context problem --- UGCoP --- car ownership --- car use --- built environment --- spatial autocorrelation --- multilevel Bayesian model --- geographical accessibility --- Healthcare services --- GIS --- E2SFCA --- CHAS --- Singapore --- environmental health --- food environment --- environmental context cube --- environmental context exposure index --- the uncertain geographic context problem (UGCoP) --- GPS --- GIS --- healthcare accessibility --- catchment areas --- access probability --- taxi GPS trajectories --- E2SFCA --- greenspace exposure --- health --- human mobility --- physical activity --- structural equation modeling --- Guangzhou --- healthcare accessibility --- population demand --- geographic impedance --- the elderly --- urban planning --- 3SFCA --- real-time traffic --- crowdedness --- well-being experience --- long-distance walking --- collective leisure activity --- walking event --- urban leisure --- missing data --- spatial data --- imputation --- geographic imputation --- activity space --- ecological momentary assessment --- EMA --- walking --- active travel --- ageing --- physical environment --- personal projects --- activity space --- Public Participatory GIS (PPGIS) --- spatial accessibility --- multimodal network --- primary healthcare --- China --- 2009 influenza A(H1N1) pandemic --- transport modes --- rail travel --- spatial spread --- quantile regression --- green space --- road traffic accidents --- cognitive aging --- activity space --- life-course perspectives --- environmental exposures

3D Remote Sensing Applications in Forest Ecology: Composition, Structure and Function

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ISBN: 9783039217823 9783039217830 Year: Pages: 188 DOI: 10.3390/books978-3-03921-783-0 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Biology --- Ecology
Added to DOAB on : 2019-12-09 11:49:16
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Dear Colleagues, The composition, structure and function of forest ecosystems are the key features characterizing their ecological properties, and can thus be crucially shaped and changed by various biotic and abiotic factors on multiple spatial scales. The magnitude and extent of these changes in recent decades calls for enhanced mitigation and adaption measures. Remote sensing data and methods are the main complementary sources of up-to-date synoptic and objective information of forest ecology. Due to the inherent 3D nature of forest ecosystems, the analysis of 3D sources of remote sensing data is considered to be most appropriate for recreating the forest’s compositional, structural and functional dynamics. In this Special Issue of Forests, we published a set of state-of-the-art scientific works including experimental studies, methodological developments and model validations, all dealing with the general topic of 3D remote sensing-assisted applications in forest ecology. We showed applications in forest ecology from a broad collection of method and sensor combinations, including fusion schemes. All in all, the studies and their focuses are as broad as a forest’s ecology or the field of remote sensing and, thus, reflect the very diverse usages and directions toward which future research and practice will be directed.

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