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MedClick Health Recommendation Algorithm Recommending …
WebMedClick Health Recommendation Algorithm Recommending Healthcare Professionals Handling Patient Preferences and Medical Specialties Rui Miguel Dos Santos Patornilho 1 and Andr ´e Vasconcelos 1;2 1 Instituto Superior T ecnico, Department of Computer Science and Engineering, Lisboa, Portugal´ 2 Instituto de Engenharia de Sistemas e …
Actived: 3 days ago
URL: https://www.scitepress.org/PublishedPapers/2018/66721/66721.pdf
Enhancing Healthcare in Emergency Department Through …
WebEnhancing Healthcare in Emergency Department Through Patient and External Conditions Proling: A Cluster Analysis Mariana Carvalho a and Ana Borges b CIICESI, Escola Superior de Tecnologia e Gest ao, Polit ecnico do Porto,´
Healthcare Data Visualization: Geos patial and Temporal …
WebWe present a health data visualization system which emphasizes the integration of geospatial and temporal information in healthcare data. We focus on two new visualization methods we developed specifically for public health data: …
A SYSTEMATIC REVIEW OF OUTLIERS DETECTION …
WebA SYSTEMATIC REVIEW OF OUTLIERS DETECTION TECHNIQUES IN MEDICAL DATA Preliminary Study Juliano Gaspar1,2, Emanuel Catumbela1,2, Bernardo Marques1,2 and Alberto Freitas1,2 1Department of Biostatistics and Medical Informatics, Faculty of Medicine, University of Porto, Porto, Portugal 2CINTESIS - Center for Research in Health …
Health Information Systems: Background and Trends of …
WebAbstract: The paper is to study the background, opportunities, challenges, and trends of development of health information systems in Russia and worldwide. There ar e two main types of HIS: electronic medical records and clinical decision support. The key areas of their application include patient management, clinical management, diagnostics
Sensor-based Solutions for Mental Healthcare: A Systematic …
WebIn this study, we conducted a systematic literature review to identify and analyze sensor-based solutions for mental healthcare. 12 studies were identied and analyzed. The majority of the selected studies presented methods and models and were empirically evaluated and showed promising accuracy results. Different types of sensors were used to
Category: Mental health Go Health
Knowledge Management Problems in Healthcare
WebKnowledge Management Problems in Healthcare A Case Study based on the Grounded Theory Erja Mustonen-Ollila1, Helvi Nyerwanire1 and Antti Valpas2 1Department of Software Engineering and Information Management, Lappeenranta University of Technology, Lappeenranta, Finland
A SWOT Analysis of Big Data in Healthcare
WebIn second place, a SWOT analysis for big data in healthcare, where are described the strength s, weaknesses , opportunities and threats . Lastly, the discussion and conclusion, which contains a reflection on the analysis previously presented and final considerations , respectively. %$&.*5281'.
Using HL7 and DICOM to Improve Operational Workflow …
WebA radiology exam is identified by a unique accession number. This can be determined us ing the value in HL7 ORM^001 OBR -3 segment or DICOM (0008,0050) tag. Accession number is then used to join between HL7 and DICOM data to determine the accurate value using one or both data sources. 2.6 Dataset.
Health Care Financing in Developing Countries: Major …
WebThe total expenditure in Bangladesh is estimated at Taka 325.1 billion in 2012. Bangladesh spends too little resources on health care. The total health expenditure of GDP increased only slightly from 3.3% to 3.5% between 2007 and 2012, which increased of …
Qur an and Hadiths in Social Media: Messages of the Qur'an …
WebSocial media has a big impact on the lives of its users. A user at first time "unknown" can instantly become famous with social media. Vice versa, great people in a relatively short time can be "worthless" by the power of social media (Mustofa, 2016). In Islam, communication is a missionary activity and the main activity of Muslim individuals.
Demographic Factors Affecting Turnover Intention Among …
WebResults: Demographic data that influences on turnover intention are gender and work unit variable with p = 0.034 and p = 0.023. Turnover intention can be explained by gender and work unit variable of 27.7%. The accuracy of this model in predicting t urnover intention is 69.7%. Conclusions : Female nurses have a higher turnover intention than
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