This service exclusively searches for literature that cites resources. Please be aware that the total number of searchable documents is limited to those containing RRIDs and does not include all open-access literature.
The decreasing cost of obtaining high-quality calls of genomic variants and the increasing availability of clinically relevant data on such variants are important drivers for personalized oncology. To allow rational genome-based decisions in diagnosis and treatment, clinicians need intuitive access to up-to-date and comprehensive variant information, encompassing, for instance, prevalence in populations and diseases, functional impact at the molecular level, associations to druggable targets, or results from clinical trials. In practice, collecting such comprehensive information on genomic variants is difficult since the underlying data is dispersed over a multitude of distributed, heterogeneous, sometimes conflicting, and quickly evolving data sources. To work efficiently, clinicians require powerful Variant Information Systems (VIS) which automatically collect and aggregate available evidences from such data sources without suppressing existing uncertainty.
We consider how a signalling system can act as an information hub by multiplexing information arising from multiple signals. We formally define multiplexing, mathematically characterise which systems can multiplex and how well they can do it. While the results of this paper are theoretical, to motivate the idea of multiplexing, we provide experimental evidence that tentatively suggests that the NF-κB transcription factor can multiplex information about changes in multiple signals. We believe that our theoretical results may resolve the apparent paradox of how a system like NF-κB that regulates cell fate and inflammatory signalling in response to diverse stimuli can appear to have the low information carrying capacity suggested by recent studies on scalar signals. In carrying out our study, we introduce new methods for the analysis of large, nonlinear stochastic dynamic models, and develop computational algorithms that facilitate the calculation of fundamental constructs of information theory such as Kullback-Leibler divergences and sensitivity matrices, and link these methods to a new theory about multiplexing information. We show that many current models such as those of the NF-κB system cannot multiplex effectively and provide models that overcome this limitation using post-transcriptional modifications.
One of the important factors for achieving "Vision 2020" targets is the availability and accessibility of eye health information systems. This study aimed to describe eye health information systems in selected countries. The status of eye health information systems in Australia, the United States, and England was reviewed. Data were gathered from the PubMed, Scopus, and ScienceDirect databases. The main key terms used included, but were not limited to "National Action plan", "Eye Health Information System", "Database", and "Registery". Also, the websites of the World Health Organization, the International Agency for the Prevention of Blindness, and Departments of Health in the selected countries were accessed. Fifty documents and articles of 170 retrieved references related to the research goals were used in this study. In all three countries, the issue of eye health is considered to be a national health priority. Concerning data gathering, the most common point in these countries was data gathered directly (health information systems, eye registries) and indirectly (studies, projects, and surveillance systems) by the organizations that participated in eye health programs. Producing accessible, timely, and highly quality information about eye health is one of the most important goals in the formation of eye health information systems in the selected countries, which facilitates achievement of the goals of the "Vision 2020: The Right to Sight" initiative.
Documentation of phenotype information is a priority need in biodiversity, crop modeling, breeding, ecology, and evolution research, for association studies, gene discovery, retrospective statistical analysis and data mining, QTL re-mapping, choosing cultivars, and planning crosses. Lack of access to phenotype information is still seen as a limiting factor for the use of plant genetic resources. Phenotype data are complex. Information on the context, under which they were collected, is indispensable, and the domain is continuously evolving. This study describes comprehensive data and object models supporting web interfaces for multi-site field phenotyping and data acquisition, which have been developed for Central Crop Databases within the European Cooperative Programme for Plant Genetic Resources over the years and which can be used as blueprints for phenotyping information systems. We start from the hypothesis, that entity relationship and object models useful for software development can picture domain expertise, similar as domain ontologies, and encourage a discussion of scientific information systems on modeling level. Starting from information requirements for statistical analysis, meta-analysis, and knowledge discovery, models are discussed in consideration of several standardization and modeling approaches including crop ontologies. Following an object-oriented modeling approach, we keep data and object models close together and to domain concepts. This will make database and software design better understandable and usable for domain experts and support a modular use of software artifacts to be shared across various domains of expertise. Classes and entities represent domain concepts with attributes naturally assigned to them. Field experiments with randomized plots, as typically used in the evaluation of plant genetic resources and in plant breeding, are in the focus. Phenotype observations, which can be listed as raw or aggregated data, are linked to explanatory metadata describing experimental treatments and agronomic interventions, observed traits and observation methodology, field plan and plot design, and the experiment site as a geographical entity. Based on clearly defined types, potential links to information systems in other domains (e.g., geographic information systems) can be better identified. Work flows are shown as web applications for the generation of field plans, field books, templates, upload of spreadsheet data, and images.
The more people there are who use clinical information systems (CIS) beyond their traditional intramural confines, the more promising the benefits are, and the more daunting the risks will be. This review thus explores the areas of ethical debates prompted by CIS conceptualized as smart systems reaching out to patients and citizens. Furthermore, it investigates the ethical competencies and education needed to use these systems appropriately.
Medical researches as well as the study of the Earth's surface, better still, geography are interlinked with each other; their relationship dates from antiquity. The science of Geographic Information Systems and, by extension, Geomatics engineering belongs to a discipline which is constantly developing at a global level. This sector has many applications regarding medical / epidemiological research and generally, the social sciences. Furthermore, this discipline may act as a decision making tool in the healthcare sector and it might contribute to the formulation of policies into the healthcare sector. The use of GIS so as to solve public health issues has an exponential increase and has been vital to the understanding and treatment of health problems in different geographic areas. In recent years, the use of various information technology services and software has lead health professionals to work more effectively.
Clinical information systems (CISs) have generated opportunities for meaningful improvements both in patient care and workflow but there is still a long way to perfection. Healthcare providers are still facing challenges of data exchange, management, and integration due to lack of functionality among these systems. Our objective here is to systematically review, synthesize, and summarize the literature that describes the current stage of clinical information systems, so as to assess the current state of knowledge, and identify benefits and challenges.
This study aimed to investigate the impact of health information technology (IT) on the Case Mix Index (CMI). This study was a retrospective cohort study using hospital financial data from the Office of Statewide Health Planning and Development (OSHPD) in California. A total of 309 unique hospitals were included in the study for 7 years, from 2009 to 2015, resulting in 2,135 hospital observations. The effects of health information technology (IT) on the Case Mix Index (CMI) was evaluated using dynamic panel data analysis to control endogeneity issues. This study found that more health IT adoption could lead to a lower CMI by improving coding systems. Policy makers, researchers, and healthcare providers must be cautious when interpreting the effect of health IT on the CMI. To encourage the adoption of health IT, the cost savings and reimbursement reductions resulting from health IT adoption should be compared. If any profit loss occurs (i.e., the cost savings is less than reimbursement reduction), more incentives should be provided to healthcare providers.
Achieving the Sustainable Development Goals will require data-driven public health action. There are limited publications on national health information systems that continuously generate health data. Given the need to develop these systems, we summarised their current status in low-income and middle-income countries.
The lack of interoperability between health information systems reduces the quality of care provided to patients and wastes resources. Accordingly, there is an urgent need to develop integration mechanisms among the various health information systems. The aim of this review was to investigate the interoperability requirements for heterogeneous health information systems and to summarize and present them.
This work addresses the problem of information distribution in multi-robot systems, with an emphasis on multi-UAV (unmanned aerial vehicle) applications. We present an analytical model that helps evaluate and compare different information distribution schemes in a robotic mission. It serves as a unified framework to represent the usefulness (utility) of each message exchanged by the robots. It can be used either on its own in order to assess the information distribution efficacy or as a building block of solutions aimed at optimizing information distribution. Moreover, we present multiple examples of instantiating the model for specific missions. They illustrate various approaches to defining the utility of different information types. Finally, we introduce a proof of concept showing the applicability of the model in a robotic system by implementing it in Robot Operating System 2 (ROS 2) and performing a simple simulated mission using a network emulator. We believe the introduced model can serve as a basis for further research on generic solutions for assessing or optimizing information distribution.
Although attainment of the health-related Millennium Development Goals relies on countries having adequate numbers of human resources for health (HRH) and their appropriate distribution, global understanding of the systems used to generate information for monitoring HRH stock and flows, known as human resources information systems (HRIS), is minimal. While HRIS are increasingly recognized as integral to health system performance assessment, baseline information regarding their scope and capability around the world has been limited. We conducted a review of the available literature on HRIS implementation processes in order to draw this baseline.
The year 2020 was predominated by the coronavirus disease 2019 (COVID-19) pandemic. The objective of this article is to review the areas in which clinical information systems (CIS) can be and have been utilized to support and enhance the response of healthcare systems to pandemics, focusing on COVID-19.
The purpose of this study was to describe the state of rehabilitation health information systems (HIS) in different settings, and identify key processes and actions which contribute to the development of HIS which can effectively support low- and middle-income countries (LMICs) allocate resources to health-related rehabilitation to people with disabilities. Nine case studies were conducted across different disability and developmental settings using documentary review and semi-structured key informant interviews (N = 41). Results were analysed against the six building blocks of a HIS, based on the Health Metrics Network Framework and Standards for Country Health Information Systems and existing HIS capacity. Key barriers or enablers to good disability data collection and use, were documented for each HIS component. Research results suggest there is no gold standard HIS for rehabilitation. There was broad consensus however, that effective health related disability planning requires reliable data on disability prevalence, functional status, access to rehabilitation services and functional outcomes of rehabilitation. For low-resource settings, and where routine HIS are already challenged, planning to include disability and rehabilitation foci starting with a minimum dataset on functioning, and progressively improving the system for increased utility and harmonization, is likely to be most effective and minimize the potential for overburdening fragile systems. The recommendations from this study are based on the successes and challenges of countries with established information systems, and will assist LMICs to prioritize strategic measures to strengthen the collection and use of data for rehabilitation, and progressively realize the rights of people with disabilities.
Immunization is one of the most important public health interventions to contrast infectious disease; however, many people nowadays refuse vaccination. Vaccine hesitancy (VH) is due to several factors that influence the complex decision-making process. Information technology tools might play an important role in vaccination programs. In particular, immunization information systems (IISs) have the potential to improve performance of vaccination programs and to increase vaccine uptake. This review aimed to present IIS functionalities in order to counter VH. In detail, we analyzed the automatic reminder/recall system, the interoperability of the system, the decision support system, the web page interface and the possibility to record adverse events following immunization. IIS could concretely represent a valid instrument to increase vaccine confidence, especially trust in both health-care workers and decision makers. There are not enough trials aimed to evaluate the efficacy of IIS to counter VH. Further researches might focalize on this aspect.
In developing countries, health information system (HIS) is experiencing more and more difficulties to produce quality data. The lack of reliable health related information makes it difficult to develop effective health policies. In order to understand the organization of HIS in African countries, we undertook a literature review.
Welcome to the FDI Lab - SciCrunch.org Resources search. From here you can search through a compilation of resources used by FDI Lab - SciCrunch.org and see how data is organized within our community.
You are currently on the Community Resources tab looking through categories and sources that FDI Lab - SciCrunch.org has compiled. You can navigate through those categories from here or change to a different tab to execute your search through. Each tab gives a different perspective on data.
If you have an account on FDI Lab - SciCrunch.org then you can log in from here to get additional features in FDI Lab - SciCrunch.org such as Collections, Saved Searches, and managing Resources.
Here is the search term that is being executed, you can type in anything you want to search for. Some tips to help searching:
You can save any searches you perform for quick access to later from here.
We recognized your search term and included synonyms and inferred terms along side your term to help get the data you are looking for.
If you are logged into FDI Lab - SciCrunch.org you can add data records to your collections to create custom spreadsheets across multiple sources of data.
Here are the facets that you can filter your papers by.
From here we'll present any options for the literature, such as exporting your current results.
If you have any further questions please check out our FAQs Page to ask questions and see our tutorials. Click this button to view this tutorial again.
Year:
Count: