Background: Interoperability between health information systems is a fundamental requirement to guarantee the continuity of health care for the population. The Fast Healthcare Interoperability Resource (FHIR) is the s...
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Background: Interoperability between health information systems is a fundamental requirement to guarantee the continuity of health care for the population. The Fast Healthcare Interoperability Resource (FHIR) is the standard that enables the design and development of interoperable systems with broad adoption worldwide. However, FHIR training curriculums need an easily administered web-based self-learning platform with modules to create scenarios and questions that the learner answers. This paper proposes a system for teaching FHIR that automatically evaluates the answers, providing the learner with continuous feedback and progress. Objective: We are designing and developing a learning management system for creating, applying, deploying, and automatically assessing FHIR web-based courses. Methods: The system requirements for teaching FHIR were collected through interviews with experts involved in academic and professional FHIR activities (universities and health institutions). The interviews were semistructured, recording and documenting each meeting. In addition, we used an ad hoc instrument to register and analyze all the needs to elicit the requirements. Finally, the information obtained was triangulated with the available evidence. This analysis was carried out with Atlas -ti software. For design purposes, the requirements were divided into functional and nonfunctional. The functional requirements were (1) a test and question manager, (2) an application programming interface (API) to orchestrate components, (3) a test evaluator that automatically evaluates the responses, and (4) a client application for students. Security and usability are essential nonfunctional requirements to design functional and secure interfaces. The software development methodology was based on the traditional spiral model. The end users of the proposed system are (1) the system administrator for all technical aspects of the server, (2) the teacher designing the courses, and (3) the studen
作者：
Correia, Ricardo A.Univ Turku
Biodivers Unit Turku 20014 Finland Univ Helsinki
Dept Geosci & Geog Helsinki Lab Interdisciplinary Conservat Sci HELIC Helsinki 00014 Finland Univ Helsinki
Helsinki Inst Sustainabil Sci HELSUS Helsinki 00014 Finland
Search engine data is a prime source of insights on information-seeking behaviour and such information is instrumental for the scientific study of human culture and behaviour. The gtrendsAPI R software package aims to...
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Search engine data is a prime source of insights on information-seeking behaviour and such information is instrumental for the scientific study of human culture and behaviour. The gtrendsAPI R software package aims to facilitate programmatic access to data available from the Google Trends API. Here, I introduce the functions available through this software package and provide worked examples of how to use it. I also discuss some the potential research applications and caveats of this software and the data available through it.
Electrocardiography (ECG) is the recording of the electrical activity of the heart with the help of the electrodes placed on the skin. The transmission of the ECG signal is very helpful in the field of Telemedicine. T...
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ISBN:
(纸本)9781538609668
Electrocardiography (ECG) is the recording of the electrical activity of the heart with the help of the electrodes placed on the skin. The transmission of the ECG signal is very helpful in the field of Telemedicine. This will help the doctors to view the patient's ECG who is living in the remote region. Other applications are ambulance monitoring, Intensive Care Unit (ICU) patient monitoring, home patient monitoring, etc, where Internet of Things (IoT) plays a major role in the transmission of medical data and information. In existing wireless technology like Global System for Mobile Communication (GSM), Satellite, Bluetooth, zigbee, etc., communication of data, installation and other practical difficulties are quite complex. But in IoT even long distance communication is made that much easier when compared to other methods.
There are numerous ways in which the customer experience can be improved in the hotel industry. One great way to do this is through a smart menu card system. Instead of the current system of ordering food through prin...
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ISBN:
(纸本)9781538647660
There are numerous ways in which the customer experience can be improved in the hotel industry. One great way to do this is through a smart menu card system. Instead of the current system of ordering food through printed menu cards, customers will be able to order their choice of meal through an app in the restaurants. This gives the customer complete freedom to browse through the menu and placing their order, which can then be sent to the kitchen for preparation. The app will have a very simple and easy yet effective user interface for the customers. This will reduce the need for printing multiple copies of the menu card. The menu can be easily updated and maintained by the restaurant staff as well unlike in the case of printed menu cards. The ordered items are also updated in the database and this will often avoid the misunderstanding between the customer and the waiter in case he gets served something different or eliminating false orders. Users will also be able to pay their bill through the app using net banking. This will reduce time consumption in getting the bill ready and reduce the dependency of paying through cash or credit cards. People using the app can also make reservations at their favorite restaurants as per the availability of tables that can be updated by the restaurant staff through the app. The app will also help in restaurant owners to not worry about hiring staff and waiters and in certain cases them not showing up for work. The app can also take up reviews of customers and leave recommendations to other users' benefit. The app will feature all the details of the hotels and their locations along with the menu that users can benefit from. The app will have a different set of user interface for the customers and the restaurant owners. The restaurant staff can use the app for keeping track of the food being ordered and bill payment. This will also help them keep an accurate record of the total earnings at the end of the day. This app has potentia
A breakthrough in building models for image processing came with the discovery that a convolutional neural net-work (CNN) can progressively extract higher-level represen-tations of the image content. Having high-resol...
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A breakthrough in building models for image processing came with the discovery that a convolutional neural net-work (CNN) can progressively extract higher-level represen-tations of the image content. Having high-resolution images to train CNN models is a key for optimizing the performance of image segmentation models. This paper presents a new dataset-called Flood Image (FloodIMG) database system- that was developed for flood related image processing and segmentation. We developed various Internet of Things Ap-plication programminginterfaces (IoT API) to gather flood-related images from Twitter, and US federal agencies' web servers, such as the US Geological Survey (USGS) and the De-partment of Transportation (DOT). Overall, > 9200 images of flooding events were collected, preprocessed, and formatted to make the dataset applicable for CNN training. Bounding boxes and polygon primitives were also labeled on each im-age to localize and classify an object in the image. Two use cases of FloodIMG are presented in this paper, where the Fast Region-based CNN (R-CNN) algorithm was used to estimate flood severity and depth during recent flooding events in the US. As of > 9200 images, 7,400 were categorized as training sets, whereas > 1,800 images were used for the R-CNN test -ing. Users can access the FloodIMG database freely through Kaggle platform to create more accessible, accurate, and op-timized image segmentation models. The FloodIMG workflow concludes with a visualization of colors and labels per im-age that can serve as a benchmark for flood image processing and segmentation.(c) 2023 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license ( http://***/licenses/by/4.0/ )
作者：
Kazuki NakamaeHidemasa BonoLaboratory of BioDX
PtBio Co-Creation Research Center Genome Editing Innovation Center Hiroshima University 3-10-23 Kagamiyama Higashi-Hiroshima 739-0046 Japan Laboratory of Genome Informatics
Graduate School of Integrated Sciences for Life Hiroshima University 3-10-23 Kagamiyama Higashi-Hiroshima 739-0046 Japan
Bioinformatics has become an indispensable technology in molecular biology for genome editing. In this review, we outline various bioinformatic techniques necessary for genome editing research. We first review state-o...
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Bioinformatics has become an indispensable technology in molecular biology for genome editing. In this review, we outline various bioinformatic techniques necessary for genome editing research. We first review state-of-the-art computational tools developed for genome editing studies. We then introduce a bio-digital transformation (BioDX) approach, which fully utilizes existing databases for biological innovation, and uses publicly available bibliographic full-text data and transcriptome data to survey genome editing target genes in model organism species, where substantial genomic information and annotation are readily available. We also discuss genome editing attempts in species with almost no genomic information. The transcriptome data, sequenced genomes, and functional annotations for these species are described, with a primary focus on the bioinformatic tools used for these analyses. Finally, we conclude on the need to maintain a database of genome editing resources for future development of genome editing research. Our review shows that the integration and maintenance of useful resources remains a challenge for bioinformatics research in genome editing, and that it is crucial for the research community to work together to create and maintain such databases in the future.
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