Intelligent tools for managing legal choices

2011 ◽  
Author(s):  
Marc Lauritsen
Keyword(s):  
Intelligent Tools

P3352Telemedicine transcends national boundaries in quest of creating a behemoth ami program

2019 ◽  
Vol 40 (Supplement_1) ◽  
Author(s):  
S Mehta ◽  
R Botelho ◽  
F Fernandez ◽  
F Feres ◽  
A Abizaid ◽  
...  
Keyword(s):  
Community Health Centers ◽  
Developed Countries ◽  
Population Based ◽  
Primary Pci ◽  
Small Community ◽  
Hub And Spoke ◽  
Web Based ◽  
National Boundaries ◽  
Intelligent Tools ◽  
Time Of Presentation

Abstract Background The Latin America Telemedicine Infarct Network (LATIN) has exploited the remarkable competence of telemedicine for remote guidance. In doing so, LATIN created a mammoth population-based AMI network that employed experts located several hundred miles away to guide the reperfusion strategies for almost 800,000 screened patients. In this pioneering project, telemedicine was initially utilized to guide AMI management within national confines. We speculated whether LATIN telemedicine navigation could outstrip countrywide borders. Purpose To maximally harness the vast possibilities of telemedicine for improving AMI care. Methods During its pilot phase, LATIN began as a hub and spoke, AMI system in Colombia where 20 spokes (small community health centers and rural clinics) were configured with 3 hubs that could perform Primary PCI. These sites were linked through web-based connectivity. Expert cardiologists, located 50–250 miles away in Bogota, Colombia, used sophisticated telemedicine platforms for urgent EKG diagnosis and teleconsultation of the entire AMI process. Based upon the duration of chest pain and travel time to the hub, these experts guided patients through guideline-based strategies of thrombolysis, pharmaco invasive management or primary PCI. Efficiency of the telemedicine process was measured with the new metric of time to telemedicine diagnosis (TTD). Cloud computing, GPS navigation, and numerous business intelligent tools were gradually incorporated into LATIN telemedicine. As systems became more scalable, the program was expanded to Brazil, where LATIN flourished. Over the last 18 months, LATIN telemedicine capabilities have been pressed across national boundaries. Presently, all 82 LATIN centers in Mexico are guided by experts located in Bogota, Colombia and the 7 Argentina centers channeled through Santiago, Chile. Results 784,947 patients were screened for AMI at 350 LATIN centers (Brazil 143, Colombia 118, Mexico 82, Argentina 7). Navigation pathways are depicted in the attached figure. TTD remains extremely low in all four countries, and comparable efficiency and tele-accuracy have been achieved. With expanded geographic reach, 8,448 (1.08%) patients were diagnosed with STEMI and 3,911 (46.3%) urgently reperfused, including 3,049 (78%) with Primary PCI. Time to TTD ranged between 2.8 to 5.8 minutes, with a mean of 3.5 min. Tele-accuracy was 98.5%, D2B 51 min, and in-hospital mortality 5.2%. Various other comparative metrics for the 4 countries are being gathered and will be available at the time of presentation. Conclusions LATIN demonstrates the robust ability of telemedicine to transcend national boundaries to guide AMI management. This strategy can be adopted in under-developed countries in Asia and Africa to provide an umbrella of AMI care for the millions of disadvantaged patients.

Intelligent tools for creative graphics

2020 ◽  
Author(s):  
Ariel Shamir ◽  
Niloy J. Mitra ◽  
Nobuyuki Umetani ◽  
Yuki Koyama
Keyword(s):  
Intelligent Tools

scholarly journals A Personalized Machine-Learning-Enabled Method for Efficient Research in Ethnopharmacology. The Case of the Southern Balkans and the Coastal Zone of Asia Minor

2021 ◽  
Vol 11 (13) ◽  
pp. 5826
Author(s):  
Evangelos Axiotis ◽  
Andreas Kontogiannis ◽  
Eleftherios Kalpoutzakis ◽  
George Giannakopoulos
Keyword(s):  
Machine Learning ◽  
Coastal Zone ◽  
Extraction Process ◽  
Asia Minor ◽  
Efficiency And Effectiveness ◽  
Effectiveness And Efficiency ◽  
Intelligent Tools ◽  
Southern Balkans

Ethnopharmacology experts face several challenges when identifying and retrieving documents and resources related to their scientific focus. The volume of sources that need to be monitored, the variety of formats utilized, and the different quality of language use across sources present some of what we call “big data” challenges in the analysis of this data. This study aims to understand if and how experts can be supported effectively through intelligent tools in the task of ethnopharmacological literature research. To this end, we utilize a real case study of ethnopharmacology research aimed at the southern Balkans and the coastal zone of Asia Minor. Thus, we propose a methodology for more efficient research in ethnopharmacology. Our work follows an “expert–apprentice” paradigm in an automatic URL extraction process, through crawling, where the apprentice is a machine learning (ML) algorithm, utilizing a combination of active learning (AL) and reinforcement learning (RL), and the expert is the human researcher. ML-powered research improved the effectiveness and efficiency of the domain expert by 3.1 and 5.14 times, respectively, fetching a total number of 420 relevant ethnopharmacological documents in only 7 h versus an estimated 36 h of human-expert effort. Therefore, utilizing artificial intelligence (AI) tools to support the researcher can boost the efficiency and effectiveness of the identification and retrieval of appropriate documents.

scholarly journals Improving Learner-Computer Interaction through Intelligent Learning Material Delivery Using Instructional Design Modeling

Entropy ◽  
2021 ◽  
Vol 23 (6) ◽  
pp. 668
Author(s):  
Christos Troussas ◽  
Akrivi Krouska ◽  
Cleo Sgouropoulou
Keyword(s):  
Instructional Design ◽  
Adaptive Learning ◽  
Educational Software ◽  
Learning Experience ◽  
Learning Material ◽  
Java Programming ◽  
Undergraduate University Students ◽  
Intelligent Tools ◽  
Content Based Filtering ◽  
Computer Interaction

This paper describes an innovative and sophisticated approach for improving learner-computer interaction in the tutoring of Java programming through the delivery of adequate learning material to learners. To achieve this, an instructional theory and intelligent techniques are combined, namely the Component Display Theory along with content-based filtering and multiple-criteria decision analysis, with the intention of providing personalized learning material and thus, improving student interaction. Until now, the majority of the research efforts mainly focus on adapting the presentation of learning material based on students’ characteristics. As such, there is free space for researching issues like delivering the appropriate type of learning material, in order to maintain the pedagogical affordance of the educational software. The blending of instructional design theories and sophisticated techniques can offer a more personalized and adaptive learning experience to learners of computer programming. The paper presents a fully operating intelligent educational software. It merges pedagogical and technological approaches for sophisticated learning material delivery to students. Moreover, it was used by undergraduate university students to learn Java programming for a semester during the COVID-19 lockdown. The findings of the evaluation showed that the presented way for delivering the Java learning material surpassed other approaches incorporating merely instructional models or intelligent tools, in terms of satisfaction and knowledge acquisition.

Polymeric colloidal particulate systems: intelligent tools for intracellular targeting of antileishmanial cargos

2013 ◽  
Vol 10 (12) ◽  
pp. 1633-1651 ◽  
Author(s):  
Shalini Asthana ◽  
Pramod K Gupta ◽  
Mohini Chaurasia ◽  
Anuradha Dube ◽  
Manish K Chourasia
Keyword(s):  
Intracellular Targeting ◽  
Intelligent Tools ◽  
Particulate Systems

A Suite of Intelligent Tools for Early Detection and Prevention of Blackouts in Power Interconnections

2018 ◽  
Vol 79 (10) ◽  
pp. 1741-1755 ◽  
Author(s):  
N. I. Voropai ◽  
N. V. Tomin ◽  
D. N. Sidorov ◽  
V. G. Kurbatsky ◽  
D. A. Panasetsky ◽  
...  
Keyword(s):  
Early Detection ◽  
Intelligent Tools ◽  
Early Detection And Prevention

Web Mining Overview

2011 ◽  
pp. 2085-2089 ◽  
Author(s):  
Bamshad Mobasher
Keyword(s):  
Web Mining ◽  
Relevant Information ◽  
Content Management ◽  
Heterogeneous Data ◽  
Web Content ◽  
Web Structure ◽  
Web Structure Mining ◽  
Content Mining ◽  
E Learning ◽  
Intelligent Tools

In the span of a decade, the World Wide Web has been transformed from a tool for information sharing among researchers into an indispensable part of everyday activities. This transformation has been characterized by an explosion of heterogeneous data and information available electronically, as well as increasingly complex applications driving a variety of systems for content management, e-commerce, e-learning, collaboration, and other Web services. This tremendous growth, in turn, has necessitated the development of more intelligent tools for end users as well as information providers in order to more effectively extract relevant information or to discover actionable knowledge. From its very beginning, the potential of extracting valuable knowledge from the Web has been quite evident. Web mining (i.e. the application of data mining techniques to extract knowledge from Web content, structure, and usage) is the collection of technologies to fulfill this potential. In this article, we will summarize briefly each of the three primary areas of Web mining—Web usage mining, Web content mining, and Web structure mining— and discuss some of the primary applications in each area.

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