A Real-time Dynamic Simulation Scheme for Large-Scale Flood Hazard Using 3D Real World Data

2007 ◽  
Author(s):  
C Wang ◽  
T. R. Wan ◽  
I. J. Palmer
Keyword(s):  
Real Time ◽  
Dynamic Simulation ◽  
Real World ◽  
Large Scale ◽  
Flood Hazard ◽  
Real World Data ◽  
World Data ◽  
Time Dynamic ◽  
Simulation Scheme

Activities for Students: As the Ball Rolls: A Quadratic Investigation Using Multiple Representations

2009 ◽  
Vol 103 (1) ◽  
pp. 62-68
Author(s):  
Kathleen Cage Mittag ◽  
Sharon Taylor
Keyword(s):  
Data Collection ◽  
Real Time ◽  
Physical Model ◽  
Real World ◽  
Graphing Calculator ◽  
Data Sets ◽  
Real World Data ◽  
World Data ◽  
Hands On ◽  
Modeling Data

Using activities to create and collect data is not a new idea. Teachers have been incorporating real-world data into their classes since at least the advent of the graphing calculator. Plenty of data collection activities and data sets exist, and the graphing calculator has made modeling data much easier. However, the authors were in search of a better physical model for a quadratic. We wanted students to see an actual parabola take shape in real time and then explore its characteristics, but we could not find such a hands-on model.

scholarly journals Exploring the Feasibility of Using Real-World Data from a Large Clinical Data Research Network to Simulate Clinical Trials of Alzheimer’s Disease

2020 ◽  
Author(s):  
Zhaoyi Chen ◽  
Hansi Zhang ◽  
Yi Guo ◽  
Thomas J George ◽  
Mattia Prosperi ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Clinical Trials ◽  
Clinical Data ◽  
Real World ◽  
Large Scale ◽  
Research Network ◽  
Real World Data ◽  
World Data ◽  
Trial Simulation

AbstractClinical trials are essential but often have high financial costs and long execution time. Trial simulation using real world data (RWD) could potentially provide insights on a treatment’s efficacy and safety before running a large-scale trial. In this work, we explored the feasibility of using RWD from a large clinical data research network to simulate a randomized controlled trial of Alzheimer’s disease considering two different scenarios: an one-arm simulation of the standard-of-care control arm; and a two-arm simulation comparing treatment safety between the intervention and control arms with proper patient matching algorithms. We followed original trial’s design and addressed some key questions, including how to translate trial criteria to database queries and establish measures of safety (i.e., serious adverse events) from RWD. Our simulation generated results comparable to the original trial, but also exposed gaps in both trial simulation methodology and the generalizability issue of clinical trials.

scholarly journals 590. Vancomycin Infusion: Algorithmic Analysis of Unstructured Real-World Data Captured from Automated Infusion Devices

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S358-S358
Author(s):  
David L Bostick ◽  
Kalvin Yu ◽  
Cynthia Yamaga ◽  
Ann Liu-Ferrara ◽  
Didier Morel ◽  
...  
Keyword(s):  
Real Time ◽  
Real World ◽  
Large Scale ◽  
Scale Up ◽  
Patient Specific ◽  
Care Practice ◽  
Becton Dickinson ◽  
Real World Data ◽  
Large Patient ◽  
Infusion Devices

Abstract Background Large scale research on antimicrobial usage in real-world populations traditionally does not consist of infusion data. With automation, detailed infusion events are captured in device systems, providing opportunities to harness them for patient safety studies. However, due to the unstructured nature of infusion data, the scale-up of data ingestion, cleansing, and processing is challenging. Figure 1. Illustration of dosing complexity Methods We applied algorithmic techniques to quantitate and visualize vancomycin administration data captured in real-time by automated infusion devices from 3 acute care hospitals. The device data included timestamped infusion events – infusion started, paused, restarted, alarmed, and stopped. We used time density-based segmentation algorithms to depict infusion sessions as bursts of event activity. We examined clinical interpretability of the cluster-defined sessions in defining infusion events, dosing intensity, and duration. Results The algorithms identified 13,339 vancomycin infusion sessions from 2,417 unique patients (mean = 5.5 sessions per patient). Clustering captured vancomycin infusion sessions consistently with correct event labels in >98% of cases. It disentangled ambiguity associated with unexpected events (e.g. multiple stopped/started events within a single infusion session). Segmentation of vancomycin infusion events on an example patient timeline is illustrated in Figure 1. The median duration of infusion sessions was 1.55 (1st, 3rd quartiles: 1.14, 2.02) hours, demonstrating clinical plausibility. Conclusion Passively captured vancomycin administration data from automated infusion device systems provide ramifications for real-time bed-side patient care practice. With large volume of data, temporal event segmentation can be an efficient approach to generate clinically interpretable insights. This method scales up accuracy and consistency in handling longitudinal dosing data. It can enable real-time population surveillance and patient-specific clinical decision support for large patient populations. Better understanding of infusion data may also have implications for vancomycin pharmacokinetic dosing. Disclosures David L. Bostick, PhD, Becton, Dickinson and Co. (Employee) Kalvin Yu, MD, Becton, Dickinson and Company (Employee)GlaxoSmithKline plc. (Other Financial or Material Support, Funding) Cynthia Yamaga, PharmD, BD (Employee) Ann Liu-Ferrara, PhD, Becton, Dickinson and Co. (Employee) Didier Morel, PhD, Becton, Dickinson and Co. (Employee) Ying P. Tabak, PhD, Becton, Dickinson and Co. (Employee)

scholarly journals Yokoyama procedure for esotropia associated with high myopia: real‐world data from a large‐scale multicentre analysis

2021 ◽  
Author(s):  
Bettina Wabbels ◽  
Julia Fricke ◽  
Michael Schittkowski ◽  
Michael Gräf ◽  
Birgit Lorenz ◽  
...  
Keyword(s):  
Real World ◽  
High Myopia ◽  
Large Scale ◽  
Real World Data ◽  
World Data
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