scholarly journals Layer-Edge Patterns Exploration and Presentation in Multiplex Networks: From Detail to Overview via Selections and Aggregations

Electronics ◽  
2019 ◽  
Vol 8 (4) ◽  
pp. 387 ◽  
Author(s):  
Xitao Zhang ◽  
Lingda Wu ◽  
Shaobo Yu ◽  
Kang Li
Keyword(s):  
Real World ◽  
Topological Structure ◽  
Visual Analysis ◽  
Layer Structure ◽  
Real World Data ◽  
Multiplex Networks ◽  
Level Information ◽  
Interlayer Structure ◽  
High Level ◽  
Multiple Interactions

Multiplex networks have been widely used to describe the multi-type connections of entities in the real world. However, researches for multiplex networks visualization unilaterally focus on the presentation of topological structure, lacking of specific high-level information presentation for quantitative comparison of interlayer structure. Users cannot participate in the exploration and freely choose the layers (or sub-graphs, regions, etc.) of interest for structural comparison. Contraposing the layer-edge patterns visual analysis tasks of multiplex networks, this paper puts forward a novel solution for exploration and analysis that tightly couples topological structure and high-level patterns. It mainly contains a multi-force directed model to realize the balanced layout of nodes in multi-layer topology, as well as two kinds of high-level patterns of which the visual representations are, respectively, designed by a familiar metaphor—that is, the similar pattern representation based on the area-proportional Venn diagrams and the interaction pattern representation based on the directed arrows. Furthermore, views association is implemented through underlying data sharing and multiple interactions which can be used to gain insights through the creation of selections of interest and produce high-level infographic-style overviews simultaneously. The experiments on real-world data demonstrate the support of the proposed method for layer-edge patterns analysis tasks in multiplex networks and the effectiveness for analyzing the multi-layer structure of multiplex networks.

scholarly journals DPUK Cohort Explorer: An Interactive Visualisation Tool

2020 ◽  
Vol 5 (5) ◽  
Author(s):  
Laura North
Keyword(s):  
Real World ◽  
Data Transfer ◽  
Real World Data ◽  
World Data ◽  
Visualisation Tool ◽  
Field Level ◽  
Level Information ◽  
Data Portal ◽  
Portal Website ◽  
Interactive Visualisation

IntroductionThe Dementias Platform UK (DPUK) Cohort Explorer is an interactive, online visualisation tool that allows users to explore data for a number of DPUK cohorts. Over 30 variables across cohorts have been harmonised, including information on demographics, lifestyle, cognition, health, and genetic biomarkers. Objectives and ApproachThe tool has been developed to complement existing DPUK cohort metadata to provide a visual representation of participant numbers and field-level information for a selection of cohorts. This enables users to determine a cohort’s eligibility before applying for access to a cohort’s data, and aid in shaping potential hypotheses. Developed using Microsoft PowerBI, the Explorer hosts a subset of the cohort’s baseline, harmonised data, allowing a user to interrogate the visualisations of the uploaded data in a secure manner on the DPUK Data Portal website. Visualisations are linked so that participant numbers and distributions can be explored interactively. ResultsThis approach allows the user to explore the harmonised data across a number of cohorts simultaneously whilst setting and adjusting filters that are of interest to the user’s search criteria. This provides a better understanding of the real-world data and enables the user to determine the feasibility of each cohort for potential studies, whilst facilitating meaningful comparisons across cohorts. The tool currently visualises five DPUK cohorts with a total of 82,391 participants, however it is being incrementally developed with more cohorts being added continually. Conclusion / ImplicationsBy combing an easy-to-use, interactive dashboard with harmonised sets of real-world data, the tool allows the user to explore, interrogate and better understand field-level information in a secure manner with zero data transfer. This provides more insight for the user when applying for access to a cohort dataset using the DPUK Data Portal and may help the user to make more informed decisions and/or hypotheses.

Neural Correlates of Fixated Low- and High-level Scene Properties during Active Scene Viewing

2020 ◽  
Vol 32 (10) ◽  
pp. 2013-2023
Author(s):  
John M. Henderson ◽  
Jessica E. Goold ◽  
Wonil Choi ◽  
Taylor R. Hayes
Keyword(s):  
Real World ◽  
Visual Analysis ◽  
Scene Perception ◽  
Active Vision ◽  
Semantic Content ◽  
Retrosplenial Cortex ◽  
Edge Density ◽  
Visual Stream ◽  
Lateral Occipital Complex ◽  
High Level

During real-world scene perception, viewers actively direct their attention through a scene in a controlled sequence of eye fixations. During each fixation, local scene properties are attended, analyzed, and interpreted. What is the relationship between fixated scene properties and neural activity in the visual cortex? Participants inspected photographs of real-world scenes in an MRI scanner while their eye movements were recorded. Fixation-related fMRI was used to measure activation as a function of lower- and higher-level scene properties at fixation, operationalized as edge density and meaning maps, respectively. We found that edge density at fixation was most associated with activation in early visual areas, whereas semantic content at fixation was most associated with activation along the ventral visual stream including core object and scene-selective areas (lateral occipital complex, parahippocampal place area, occipital place area, and retrosplenial cortex). The observed activation from semantic content was not accounted for by differences in edge density. The results are consistent with active vision models in which fixation gates detailed visual analysis for fixated scene regions, and this gating influences both lower and higher levels of scene analysis.

scholarly journals Locational privacy-preserving distance computations with intersecting sets of randomly labeled grid points

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Rainer Schnell ◽  
Jonas Klingwort ◽  
James M. Farrow
Keyword(s):  
Programming Languages ◽  
Real World ◽  
Spatial Data ◽  
Large Scale ◽  
Privacy Preserving ◽  
Real World Data ◽  
Data Set ◽  
Additional Information ◽  
Grid Points ◽  
High Level

Abstract Background We introduce and study a recently proposed method for privacy-preserving distance computations which has received little attention in the scientific literature so far. The method, which is based on intersecting sets of randomly labeled grid points, is henceforth denoted as ISGP allows calculating the approximate distances between masked spatial data. Coordinates are replaced by sets of hash values. The method allows the computation of distances between locations L when the locations at different points in time t are not known simultaneously. The distance between $$L_1$$ L 1 and $$L_2$$ L 2 could be computed even when $$L_2$$ L 2 does not exist at $$t_1$$ t 1 and $$L_1$$ L 1 has been deleted at $$t_2$$ t 2 . An example would be patients from a medical data set and locations of later hospitalizations. ISGP is a new tool for privacy-preserving data handling of geo-referenced data sets in general. Furthermore, this technique can be used to include geographical identifiers as additional information for privacy-preserving record-linkage. To show that the technique can be implemented in most high-level programming languages with a few lines of code, a complete implementation within the statistical programming language R is given. The properties of the method are explored using simulations based on large-scale real-world data of hospitals ($$n=850$$ n = 850 ) and residential locations ($$n=13,000$$ n = 13 , 000 ). The method has already been used in a real-world application. Results ISGP yields very accurate results. Our simulation study showed that—with appropriately chosen parameters – 99 % accuracy in the approximated distances is achieved. Conclusion We discussed a new method for privacy-preserving distance computations in microdata. The method is highly accurate, fast, has low computational burden, and does not require excessive storage.

scholarly journals Systems AI: A Declarative Learning Based Programming Perspective

2018 ◽  
Author(s):  
Parisa Kordjamshidi ◽  
Dan Roth ◽  
Kristian Kersting
Keyword(s):  
Machine Learning ◽  
Real World ◽  
Data Driven ◽  
Real World Data ◽  
Future Directions ◽  
Knowledge Representations ◽  
Real World Applications ◽  
Need To Evaluate ◽  
Declarative Learning ◽  
High Level

Data-driven approaches are becoming dominant problem-solving techniques in many areas of research and industry. Unfortunately, current technologies do not make such techniques easy to use for application experts who are not fluent in machine learning nor for machine learning experts who aim at testing ideas on real-world data and need to evaluate those as a part of an end-to-end system. We review key efforts made by various AI communities to provide languages for high-level abstractions over learning and reasoning techniques needed for designing complex AI systems. We classify the existing frameworks based on the type of techniques as well as the data and knowledge representations they use, provide a comparative study of the way they address the challenges of programming real-world applications, and highlight some shortcomings and future directions.

scholarly journals AMS-Net: An Attention-Based Multi-Scale Network for Classification of 3D Terracotta Warrior Fragments

2021 ◽  
Vol 13 (18) ◽  
pp. 3713
Author(s):  
Jie Liu ◽  
Xin Cao ◽  
Pingchuan Zhang ◽  
Xueli Xu ◽  
Yangyang Liu ◽  
...  
Keyword(s):  
Real World ◽  
Data Sets ◽  
Semantic Features ◽  
Real World Data ◽  
Global Features ◽  
Data Set ◽  
Multi Scale ◽  
Public Data ◽  
High Level

As an essential step in the restoration of Terracotta Warriors, the results of fragments classification will directly affect the performance of fragments matching and splicing. However, most of the existing methods are based on traditional technology and have low accuracy in classification. A practical and effective classification method for fragments is an urgent need. In this case, an attention-based multi-scale neural network named AMS-Net is proposed to extract significant geometric and semantic features. AMS-Net is a hierarchical structure consisting of a multi-scale set abstraction block (MS-BLOCK) and a fully connected (FC) layer. MS-BLOCK consists of a local-global layer (LGLayer) and an improved multi-layer perceptron (IMLP). With a multi-scale strategy, LGLayer can parallel extract the local and global features from different scales. IMLP can concatenate the high-level and low-level features for classification tasks. Extensive experiments on the public data set (ModelNet40/10) and the real-world Terracotta Warrior fragments data set are conducted. The accuracy results with normal can achieve 93.52% and 96.22%, respectively. For real-world data sets, the accuracy is best among the existing methods. The robustness and effectiveness of the performance on the task of 3D point cloud classification are also investigated. It proves that the proposed end-to-end learning network is more effective and suitable for the classification of the Terracotta Warrior fragments.

VP116 Comparison Between Time To Off Treatment And Italian Medicines Agency Registries Treatment Duration

2017 ◽  
Vol 33 (S1) ◽  
pp. 203-204
Author(s):  
Gabriele Vittoria ◽  
Antonio Fascì ◽  
Matteo Ferrario ◽  
Giovanni Giuliani
Keyword(s):  
Clinical Trials ◽  
Real World ◽  
Treatment Duration ◽  
National Level ◽  
Real Life ◽  
Evidence Base ◽  
Phase Iii ◽  
Real World Data ◽  
The Mean ◽  
High Level

INTRODUCTION:The Italian Medicines Agency Registry represents a tool that could be a precious source of information regarding the mean treatment duration of a drug in a real world context. Monitoring registries are applied at the national level after market authorization and are designed not only to apply the Managed Entry Agreements (MEAs) but also to collect Real World Data on drugs safety, effectiveness and real life utilization. The purpose of this analysis was to compare the treatment duration from clinical trials and the mean treatment duration calculated using data from monitoring registries (1).METHODS:For each drug included in the analysis it was collected the treatment duration from Time To Off Treatment curves for the experimental drug (eTTOT) from Phase III clinical trials and the mean treatment duration data calculated by using the number of cycles (converted in months of treatment) of all treated patients extracted from AIFA registries (TTAR). The mean ratios between the Time of Treatment of Italian Medicines Agency and Experimental arm time to off treatment were calculated to identify potential correlations. High level of correlation was expected if Time to Payment By Result /Time To Off Treatment ratio was close to 1 (±.2).RESULTS:Six Roche products or different indications of the same product were identified as candidates for the analysis from 2013 to 2016. The mean TTAR/eTTOT ratio observed in patients treated from 2013 to 2016 was .97 (±.10), meaning that the mean treatment duration calculated from AIFA Registries is strongly comparable with the treatment duration observed in clinical trials. In one case the TTAR is even more major than eTTOT.CONCLUSIONS:A high level of correlation between TTAR and eTTOT was found. Additional analyses considering different cohorts of patients over time could be useful to have a more precise estimate of real world drug utilization. Even though RCTs remain the gold standard for demonstrating clinical efficacy in restricted trial setting, Real World Evidence from AIFA registries can contribute to the evidence base needed for healthcare decisions.

scholarly journals Real World Data en la Sanidad Española

2018 ◽  
Vol 3 (1) ◽  
pp. 795
Author(s):  
Isabel De la Torre Díez ◽  
Guillermo Fernández Rodríguez ◽  
Gema Castillo ◽  
Aranzazu Berbey Alvarez
Keyword(s):  
Clinical Data ◽  
Real World ◽  
Data Sources ◽  
Real World Data ◽  
Medical Decisions ◽  
World Data ◽  
Usual Clinical Practice ◽  
Medical Histories ◽  
The Government ◽  
High Level

In recent years, thanks to the progress of electronics and computing, it is possible to process a large volume of clinical data. As a result of this scenario, real world data (RWD) are gaining enormous relevance. RWD are the data, whose origin is the usual clinical practice, used to make medical decisions about drugs or medical practice. This research is aimed to study the current situation of RWD in Spain. To achieve this objective, we have assessed the data sources on which these are fed. We have also analyzed the main publications based on RWD. Our findings are: firstly, both records and databases as well as medical histories have a high level of computerization and have also a great deal of information to be used for research; and secondly, the scientific studies carried out are of a great quality, but society is not aware of the importance RWD have and there is discoordination between the Autonomies and the Government. Keywords: RWD, clinical data, medical decisions, practical decisions, medical histories

Abstract #946: Assessment of Acromegaly Patients with and Without Diabetes Treated with Lanreotide Depot: 2-Year Real World Data

2016 ◽  
Vol 22 ◽  
pp. 219
Author(s):  
Roberto Salvatori ◽  
Olga Gambetti ◽  
Whitney Woodmansee ◽  
David Cox ◽  
Beloo Mirakhur ◽  
...  
Keyword(s):  
Real World ◽  
Real World Data ◽  
World Data

Safety and efficacy of direct acting oral anticoagulants and vitamin K antagonists in nonvalvular atrial fibrillation – a network meta-analysis of real-world data

VASA ◽  
2019 ◽  
Vol 48 (2) ◽  
pp. 134-147 ◽  
Author(s):  
Mirko Hirschl ◽  
Michael Kundi
Keyword(s):  
Real World ◽  
Meta Analysis ◽  
Vitamin K Antagonists ◽  
Oral Anticoagulants ◽  
Efficacy And Safety ◽  
Nonvalvular Atrial Fibrillation ◽  
Real World Data ◽  
Hazard Ratios ◽  
Direct Acting ◽  
Event Rates

Abstract. Background: In randomized controlled trials (RCTs) direct acting oral anticoagulants (DOACs) showed a superior risk-benefit profile in comparison to vitamin K antagonists (VKAs) for patients with nonvalvular atrial fibrillation. Patients enrolled in such studies do not necessarily reflect the whole target population treated in real-world practice. Materials and methods: By a systematic literature search, 88 studies including 3,351,628 patients providing over 2.9 million patient-years of follow-up were identified. Hazard ratios and event-rates for the main efficacy and safety outcomes were extracted and the results for DOACs and VKAs combined by network meta-analysis. In addition, meta-regression was performed to identify factors responsible for heterogeneity across studies. Results: For stroke and systemic embolism as well as for major bleeding and intracranial bleeding real-world studies gave virtually the same result as RCTs with higher efficacy and lower major bleeding risk (for dabigatran and apixaban) and lower risk of intracranial bleeding (all DOACs) compared to VKAs. Results for gastrointestinal bleeding were consistently better for DOACs and hazard ratios of myocardial infarction were significantly lower in real-world for dabigatran and apixaban compared to RCTs. By a ranking analysis we found that apixaban is the safest anticoagulant drug, while rivaroxaban closely followed by dabigatran are the most efficacious. Risk of bias and heterogeneity was assessed and had little impact on the overall results. Analysis of effect modification could guide the clinical decision as no single DOAC was superior/inferior to the others under all conditions. Conclusions: DOACs were at least as efficacious as VKAs. In terms of safety endpoints, DOACs performed better under real-world conditions than in RCTs. The current real-world data showed that differences in efficacy and safety, despite generally low event rates, exist between DOACs. Knowledge about these differences in performance can contribute to a more personalized medicine.

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