Analytical Approach for Virtual Classification of e-Health Interventions and Medical Data Sources Integration

2019 ◽  
pp. 286-297
Author(s):  
Cherrat Loubna ◽  
Khrouch Sarah ◽  
Ezziyyani Mostafa
Keyword(s):  
Analytical Approach ◽  
Medical Data ◽  
Health Interventions ◽  
Data Sources

scholarly journals An updated classification of the jumping plant-lice (Hemiptera: Psylloidea) integrating molecular and morphological evidence

2021 ◽  
Vol 736 ◽  
pp. 137-182
Author(s):  
Daniel Burckhardt ◽  
David Ouvrard ◽  
Diana M. Percy
Keyword(s):  
New Species ◽  
New Genus ◽  
Molecular Data ◽  
Data Sources ◽  
Morphological Evidence ◽  
Sampling Strategies ◽  
Molecular Studies ◽  
Family Level ◽  
A New Species

The classification of the superfamily Psylloidea is revised to incorporate findings from recent molecular studies, and to integrate a reassessment of monophyla primarily based on molecular data with morphological evidence and previous classifications. We incorporate a reinterpretation of relevant morphology in the light of the molecular findings and discuss conflicts with respect to different data sources and sampling strategies. Seven families are recognised of which four (Calophyidae, Carsidaridae, Mastigimatidae and Triozidae) are strongly supported, and three (Aphalaridae, Liviidae and Psyllidae) weakly or moderately supported. Although the revised classification is mostly similar to those recognised by recent authors, there are some notable differences, such as Diaphorina and Katacephala which are transferred from Liviidae to Psyllidae. Five new subfamilies and one new genus are described, and one secondary homonym is replaced by a new species name. A new or revised status is proposed for one family, four subfamilies, four tribes, seven subtribes and five genera. One tribe and eight genera / subgenera are synonymised, and 32 new and six revised species combinations are proposed. All recognised genera of Psylloidea (extant and fossil) are assigned to family level taxa, except for one which is considered a nomen dubium.

scholarly journals Towards a Language-Based Typology of Church Names in Ghana

2021 ◽  
pp. 77-87
Author(s):  
Osei Yaw Akoto ◽  
Juliet Oppong-Asare Ansah
Keyword(s):  
Content Analysis ◽  
Analytical Approach ◽  
The Other ◽  
English Only ◽  
Other Hand

Over the years, scholars have sought to provide language-based typologies of names, but while attempts have been made for some sub-branches of onomastics such as anthroponymy and toponymy, there is arguably none for ecclesionymy (the study of church names). Consequently, this paper sought to provide a language based typology of the hitherto underexplored area of church names. Data of names of churches in Ghana was built for the present study. Adopting content analysis as the analytical approach, the study realized that church names in Ghana are generally homogenous and heterogeneous linguistically. It was also realized that homogenous/unilingual church names involved English only, Akan only and Ewe only. On the other hand, the heterogeneous church names comprised two types: bilingual and trilingual church names, which contained varied language permutations from the three spheres in Osei Yaw Akoto’s classification of languages in Ghana. The paper concludes by making some recommendations for language-in-religion policy in Ghana. Keywords: Church names, Ecclesionymy, Glocal language, Unilingual

Proposal of Analytical Model for Business Problems Solving in Big Data Environment

Web Services ◽  
2019 ◽  
pp. 618-638
Author(s):  
Goran Klepac ◽  
Kristi L. Berg
Keyword(s):  
Data Mining ◽  
Big Data ◽  
Predictive Models ◽  
Analytical Approach ◽  
Fraud Detection ◽  
Analytical Techniques ◽  
Data Sources ◽  
Business Decisions ◽  
Mining Projects ◽  
Structured Approach

This chapter proposes a new analytical approach that consolidates the traditional analytical approach for solving problems such as churn detection, fraud detection, building predictive models, segmentation modeling with data sources, and analytical techniques from the big data area. Presented are solutions offering a structured approach for the integration of different concepts into one, which helps analysts as well as managers to use potentials from different areas in a systematic way. By using this concept, companies have the opportunity to introduce big data potential in everyday data mining projects. As is visible from the chapter, neglecting big data potentials results often with incomplete analytical results, which imply incomplete information for business decisions and can imply bad business decisions. The chapter also provides suggestions on how to recognize useful data sources from the big data area and how to analyze them along with traditional data sources for achieving more qualitative information for business decisions.

scholarly journals A Three-Phase Decision Model of Computer-Aided Coding for the Iranian Classification of Health Interventions (IRCHI)

2017 ◽  
Vol 25 (2) ◽  
pp. 88 ◽  
Author(s):  
Zahra Azadmanjir ◽  
Reza Safdari ◽  
Marjan Ghazisaeedi ◽  
Mehrshad Mokhtaran ◽  
Mohammad Kameli
Keyword(s):  
Decision Model ◽  
Health Interventions ◽  
Three Phase ◽  
Computer Aided

scholarly journals A Fog Computing-Based Architecture for Medical Records Management

2019 ◽  
Vol 2019 ◽  
pp. 1-16 ◽  
Author(s):  
Cícero A. Silva ◽  
Gibeon S. Aquino ◽  
Sávio R. M. Melo ◽  
Dannylo J. B. Egídio
Keyword(s):  
Medical Records ◽  
Fog Computing ◽  
Medical Data ◽  
Data Sources ◽  
Medical Applications ◽  
Records Management ◽  
Medical Field ◽  
Computing Paradigm ◽  
And Storage

The aging of the world’s population and the growth in the number of people with chronic diseases have increased expenses with medical care. Thus, the use of technological solutions has been widely adopted in the medical field to improve the patients’ health. In this context, approaches based on Cloud Computing have been used to store and process the information generated in these solutions. However, using Cloud can create delays that are intolerable for medical applications. Thus, the Fog Computing paradigm emerged as an alternative to overcome this problem, bringing computation and storage closer to the data sources. However, managing medical data stored in Fog is still a challenge. Moreover, characteristics of availability, performance, interoperability, and privacy need to be considered in approaches that aim to explore this problem. So, this article shows a software architecture based on Fog Computing and designed to facilitate the management of medical records. This architecture uses Blockchain concepts to provide the necessary privacy features and to allow Fog Nodes to carry out the authorization process in a distributed way. Finally, this paper describes a case study that evaluates the performance, privacy, and interoperability requirements of the proposed architecture in a home-centered healthcare scenario.

Medical Reports Analysis Using Natural Language Processing for Disease Classification

2020 ◽  
pp. 155-172
Author(s):  
Sumathi S. ◽  
Indumathi S. ◽  
Rajkumar S.
Keyword(s):  
Natural Language Processing ◽  
Language Processing ◽  
Text Classification ◽  
Medical Data ◽  
Disease Classification ◽  
Human Interaction ◽  
Time Consumption ◽  
Medical Reports ◽  
Medical Documents

Text classification in medical domain could result in an easier way of handling large volumes of medical data. They can be segregated depending on the type of diseases, which can be determined by extracting the decisive key texts from the original document. Due to various nuances present in understanding language in general, a requirement of large volumes of text-based data is required for algorithms to learn patterns properly. The problem with existing systems such as MedScape, MedLinePlus, Wrappin, and MedHunt is that they involve human interaction and high time consumption in handling a large volume of data. By employing automation in this proposed field, the large involvement of manpower could be removed which in turn speeds up the process of classification of the medical documents by which the shortage of medical technicians in third world countries are addressed.

Data capture for injury prevention

2020 ◽  
Vol 26 (4) ◽  
pp. 391-394 ◽  
Author(s):  
Yvette Holder
Keyword(s):  
Missing Data ◽  
Data Collection ◽  
Data Capture ◽  
Data Sources ◽  
Surveillance Systems ◽  
New Developments ◽  
Coding Systems ◽  
Wide Range ◽  
Data Elements

More than a half-century of developments have expanded the demand for data for the prevention of injuries. This article follows the progress as data collection becomes more comprehensive, encompassing all types of injuries, in a wide range of economic and cultural environments. It describes the challenges of new developments and the responses to deal with them, challenges of poor coordination of data sources, sector ownership, non-uniformity and missing data elements that are critical for prevention. The tools and approaches that may be employed are outlined, from observatories to surveillance systems, from standardised injury coding systems such as the International Classification of External Cause of Injuries to manuals and guidelines for collecting injury data through surveillance and surveys. More and better data encourages greater utilisation which in turn identifies new issues to be addressed, a most exciting situation for any injury practitioner.

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