scholarly journals Parrot: A Progressive Analysis System on Large Text Collections

Author(s):  
Yazhong Zhang ◽  
Hanbing Zhang ◽  
Zhenying He ◽  
Yinan Jing ◽  
Kai Zhang ◽  
...  

Abstract The size of textual data continues to grow along with the need for timely and cost-effective analysis, while the growth of computation power cannot keep up with the growth of data. The delays when processing huge textual data can negatively impact user activity and insight. This calls for a paradigm shift from blocking fashion to progressive processing. In this paper, we propose a sample-based progressive processing model that focuses on term frequency calculation on text. The model is based on an incremental execution engine and will calculate a series of approximate results for a single query in a progressive way to provide a smooth trade-off between accuracy and latency. As a part, we proposed a new variant of the bootstrap technique to quantify result error progressively. We implemented this method in our system called Parrot on top of Apache Spark and used real-world data to test its performance. Experiments demonstrate that our method is 2.4×–19.7× faster to get a result within 1% error while the confidence interval always covers the accurate results very well.

2017 ◽  
Vol 26 (1) ◽  
pp. 53-62 ◽  
Author(s):  
Richard Bell ◽  
Braden Te Ao ◽  
Natasha Ironside ◽  
Adam Bartlett ◽  
John A. Windsor ◽  
...  

Author(s):  
Alexis K. Okoh ◽  
Emaad Siddiqui ◽  
Cassandra Soto ◽  
Nehal Dhaduk ◽  
Sameer Hirji ◽  
...  

Objective The current study aims to report trends of early discharges and identify associated direct costs using a nationally representative database of real-world data experience. Methods We used nationally weighted data on all patients who had transfemoral transcatheter aortic valve replacement (TAVR) from 2012 to 2017 and discharged alive from the National Inpatient Sample. Patients were divided into early (discharge ≤3 days of admission) and late discharge. Demographics and clinical characteristics were compared. Trends in early discharge and costs associated with admissions were analyzed over the study period. Results Of the 125,188 patients identified, 59,424 (46.9%) were discharged early. The proportion of early discharge increased from 15% in early 2012 to 68% in late 2017 ( P < 0.001), with the largest increase occurring from 2014 to 2015. Overall, the average cost of TAVR decreased from $58,408 in 2012 to $49,875 in 2017 ( P < 0.001). Compared to late discharge, patients discharged early reported costs savings of ≥$20,000 over the study period. Among the early discharge group, no significant differences in costs were observed for patients discharged on 0 to 1, 2, or 3 days after the procedure. Conclusions Postoperative length of stay after TAVR has decreased dramatically within the last decade with an observed reduction in procedural costs. While discharge within 3 days appeared cost effective, no differences in costs were noted among patients discharged ≤3 days.


2021 ◽  
pp. 089719002110272
Author(s):  
Joanne Huang ◽  
Jeannie D. Chan ◽  
Thu Nguyen ◽  
Rupali Jain ◽  
Zahra Kassamali Escobar

Universal area-under-the-curve (AUC) guided vancomycin therapeutic drug monitoring (TDM) is resource-intensive, cost-prohibitive, and presents a paradigm shift that leaves institutions with the quandary of defining the preferred and most practical method for TDM. We report a step-by-step quality improvement process using 4 plan-do-study-act (PDSA) cycles to provide a framework for development of a hybrid model of trough and AUC-based vancomycin monitoring. We found trough-based monitoring a pragmatic strategy as a first-tier approach when anticipated use is short-term. AUC-guided monitoring was most impactful and cost-effective when reserved for patients with high-risk for nephrotoxicity. We encourage others to consider quality improvement tools to locally adopt AUC-based monitoring.


1999 ◽  
Vol 2 (3) ◽  
pp. 184 ◽  
Author(s):  
EA Alemao ◽  
PS Cady ◽  
HM Phatak ◽  
VL Culbertson

2008 ◽  
Vol 41 (2) ◽  
pp. 126-134 ◽  
Author(s):  
A.M.E.C. Barreto ◽  
K. Takei ◽  
Sabino E.C. ◽  
M.A.O. Bellesa ◽  
N.A. Salles ◽  
...  

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