scholarly journals HUBzero and CatalyzeCare: A community driven platform for data sharing and collaboration in medical informatics research

2017 ◽  
Author(s):  
Michael Zentner ◽  
Richard Zink
Keyword(s):  
Best Practices ◽  
Infusion Pump ◽  
Daily Basis ◽  
Treatment Unit ◽  
Infusion Pumps ◽  
Process Improvements ◽  
Professional Programs ◽  
Additional Information ◽  
The Difference ◽  
Scientific Phenomena

The HUBzero platform is an infrastructure enabling online scientific communities to collaborate and share information and computational resources as they explore scientific phenomena. HUBzero has been adopted by the Regenstrief Center for Healthcare Engineering (RCHE) at Purdue University to form the HUB CatalyzeCare. RCHE has formed the community REMEDI Central on their CatalyzeCare hub that has been adopted by more than 140 hospitals and records data from over 30,000 infusion pumps. Hospitals voluntarily contribute the alert streams emanating from smart intravenous pumps and their drug limit libraries to the REMEDI Central community. Infusion pumps emit an alert whenever a healthcare professional programs the pump to administer a dose to a patient outside of the bounds established by the hospital in their drug limit library. The drug limit library contains for each drug in each treatment unit (e.g. pediatrics, intensive care) a set of low and high limits for administration by bolus and continuous infusion. A practitioner’s response to an alert can be to reprogram the pump, to delay the infusion as they seek additional information from the ordering physician, or to override. Response to an individual alert can mean the difference between successful treatment, an adverse event, or even death. In the aggregate, alerts and their associated responses can represent the quality of hospital training, areas of improvement in procedures, or deficiencies in the hospital’s drug limit library. Across hospitals, the alerts and drug limit library entries provide a means of benchmarking and improvement. As part of the agreement for joining REMEDI Central, hospitals are able to benchmark against the other hospitals in the community. No hospital is anonymous. By agreement, the hospitals have determined that the value of the shared data is high enough that they willingly identify themselves. Collectively, their goal is to improve overall patient safety by creating a set of best practices regarding infusion pump alert mitigation and response. The REMEDI Central community members meet three times annually, and openly share with each other their best practices and process improvements. The REMEDI Central community is unique in that it has three key stakeholder types and provides distinct value to each. Hospital practitioners get immediate tactical feedback from REMEDI Central as it guides them on a daily basis with regard to infusion alerts. Hospital administrators gain a strategic view from being able to benchmark their practices against their peer facilities. Researchers gain access to a stream of data that would otherwise be unavailable for the purpose of developing research-based interventions in healthcare. Since practitioners are provided immediate value from their data, they are incentivized to provide their data on a regular basis. This immediate incentive is key for researchers to be able to access an up-to-date and growing database of information.

scholarly journals HUBzero and CatalyzeCare: A community driven platform for data sharing and collaboration in medical informatics research

2017 ◽  
Author(s):  
Michael Zentner ◽  
Richard Zink
Keyword(s):  
Best Practices ◽  
Infusion Pump ◽  
Daily Basis ◽  
Treatment Unit ◽  
Infusion Pumps ◽  
Process Improvements ◽  
Professional Programs ◽  
Additional Information ◽  
The Difference ◽  
Scientific Phenomena

The HUBzero platform is an infrastructure enabling online scientific communities to collaborate and share information and computational resources as they explore scientific phenomena. HUBzero has been adopted by the Regenstrief Center for Healthcare Engineering (RCHE) at Purdue University to form the HUB CatalyzeCare. RCHE has formed the community REMEDI Central on their CatalyzeCare hub that has been adopted by more than 140 hospitals and records data from over 30,000 infusion pumps. Hospitals voluntarily contribute the alert streams emanating from smart intravenous pumps and their drug limit libraries to the REMEDI Central community. Infusion pumps emit an alert whenever a healthcare professional programs the pump to administer a dose to a patient outside of the bounds established by the hospital in their drug limit library. The drug limit library contains for each drug in each treatment unit (e.g. pediatrics, intensive care) a set of low and high limits for administration by bolus and continuous infusion. A practitioner’s response to an alert can be to reprogram the pump, to delay the infusion as they seek additional information from the ordering physician, or to override. Response to an individual alert can mean the difference between successful treatment, an adverse event, or even death. In the aggregate, alerts and their associated responses can represent the quality of hospital training, areas of improvement in procedures, or deficiencies in the hospital’s drug limit library. Across hospitals, the alerts and drug limit library entries provide a means of benchmarking and improvement. As part of the agreement for joining REMEDI Central, hospitals are able to benchmark against the other hospitals in the community. No hospital is anonymous. By agreement, the hospitals have determined that the value of the shared data is high enough that they willingly identify themselves. Collectively, their goal is to improve overall patient safety by creating a set of best practices regarding infusion pump alert mitigation and response. The REMEDI Central community members meet three times annually, and openly share with each other their best practices and process improvements. The REMEDI Central community is unique in that it has three key stakeholder types and provides distinct value to each. Hospital practitioners get immediate tactical feedback from REMEDI Central as it guides them on a daily basis with regard to infusion alerts. Hospital administrators gain a strategic view from being able to benchmark their practices against their peer facilities. Researchers gain access to a stream of data that would otherwise be unavailable for the purpose of developing research-based interventions in healthcare. Since practitioners are provided immediate value from their data, they are incentivized to provide their data on a regular basis. This immediate incentive is key for researchers to be able to access an up-to-date and growing database of information.

scholarly journals Exploring the Use of PlanetScope Data for Particulate Matter Air Quality Research

2021 ◽  
Vol 13 (15) ◽  
pp. 2981
Author(s):  
Jeanné le Roux ◽  
Sundar Christopher ◽  
Manil Maskey
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Land Cover ◽  
Spectral Response ◽  
Fine Particulate Matter ◽  
Daily Basis ◽  
Land Cover Types ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
The Difference ◽  
Geolocation Accuracy

Planet, a commercial company, has achieved a key milestone by launching a large fleet of small satellites (smallsats) that provide high spatial resolution imagery of the entire Earth’s surface on a daily basis with its PlanetScope sensors. Given the potential utility of these data, this study explores the use for fine particulate matter (PM2.5) air quality applications. However, before these data can be utilized for air quality applications, key features of the data, including geolocation accuracy, calibration quality, and consistency in spectral signatures, need to be addressed. In this study, selected Dove-Classic PlanetScope data is screened for geolocation consistency. The spectral response of the Dove-Classic PlanetScope data is then compared to Moderate Resolution Imaging Spectroradiometer (MODIS) data over different land cover types, and under varying PM2.5 and mid visible aerosol optical depth (AOD) conditions. The data selected for this study was found to fall within Planet’s reported geolocation accuracy of 10 m (between 3–4 pixels). In a comparison of top of atmosphere (TOA) reflectance over a sample of different land cover types, the difference in reflectance between PlanetScope and MODIS ranged from near-zero (0.0014) to 0.117, with a mean difference in reflectance of 0.046 ± 0.031 across all bands. The reflectance values from PlanetScope were higher than MODIS 78% of the time, although no significant relationship was found between surface PM2.5 or AOD and TOA reflectance for the cases that were studied. The results indicate that commercial satellite data have the potential to address Earth-environmental issues.

scholarly journals Urinary Microbiome Characteristics in Female Patients with Acute Uncomplicated Cystitis and Recurrent Cystitis

2021 ◽  
Vol 10 (5) ◽  
pp. 1097
Author(s):  
Jeong-Ju Yoo ◽  
Hee Shin ◽  
Ju Song ◽  
Minjung Kim ◽  
Jina Yun ◽  
...  
Keyword(s):  
Urine Culture ◽  
Culture Methods ◽  
Microbiome Composition ◽  
Additional Information ◽  
Transurethral Catheter ◽  
Urinary Microbiome ◽  
Acute Uncomplicated Cystitis ◽  
The Difference ◽  
Uncomplicated Cystitis ◽  
Recurrent Cystitis

Traditionally, the diagnostic mainstay of recurrent urinary tract infection has been urinary culture. However, the causative uropathogen of recurrent cystitis has not been well established. Urine DNA next-generation sequencing (NGS) can provide additional information on these infections. Herein, we compared urine NGS results and urine cultures in patients with acute uncomplicated cystitis (AUC) and recurrent cystitis (RC), and evaluated the difference in microbiome patterns in the NGS results. Patients who underwent urine culture and NGS due to AUC or RC were retrospectively reviewed. All urine samples were collected via a transurethral catheter and studied utilizing a type of NGS called 16S ribosomal RNA gene amplification and sequencing. The sensitivity of urine NGS was significantly higher than that of conventional urine culture (69.0% vs. 16.7%, p < 0.05). The detection rate of urine NGS was slightly lower in the RC group than in the AUC group (67.7% vs. 72.7%). Microbiome diversity was significantly higher in the RC group compared to the AUC group (p = 0.007), and the microbiome composition was significantly different between the AUC and RC groups. In the urine NGS results, Pseudomonas, Acinetobacter, and Enterobacteriaceae were found in the AUC group, and Sphingomonas, Staphylococcus, Streptococcus, and Rothia spp. were detected in the RC group. Urine NGS can significantly increase the diagnostic sensitivity compared to traditional urine culture methods, especially in RC patients. AUC and RC patients had significant differences in bacterial diversity and patterns. Therefore, recurrent cystitis might be approached from a different perspective.

Method for the simultaneous quantification of n-hexane metabolites: application to n-hexane metabolism determination

1996 ◽  
Vol 15 (6) ◽  
pp. 497-503 ◽  
Author(s):  
T. Soriano ◽  
M. Menéndez ◽  
P. Sanz ◽  
M. Repetto
Keyword(s):  
Similar Pattern ◽  
Analytical Procedure ◽  
Daily Basis ◽  
Practical Application ◽  
Simultaneous Quantification ◽  
Exposed Workers ◽  
Before And After ◽  
Time Requirements ◽  
The Difference

1 The described analytical procedure permits the simultaneous determination of the main n-hexane meta bolites in urine. 2-Hexanone, 2-hexanol, 2, 5-hexanediol and 2, 5-hexanedione, were chosen to dose the rats used in this study. All urine samples were collected and analysed on a daily basis, before and after acidic hydrolysis (pH 0.1) by GC/MS. 2-Hexanone, 2, 5-dimethylfurane, γ-valerolac tone and 2, 5-hexanedione were determined before hydro lysis ; 2-hexanol and 2, 5-hexanediol, after hydrolysis; and 5-hydroxy-2-hexanone and 4, 5-dihydroxy-2-hexanone were calculated by the difference between γ-valerolactone and 2, 5-hexanedione with and without hydrolysis, respectively. 2 A metabolic scheme was proposed reflecting the biotransformations undergone by the four compounds assayed. We consider 2, 5-dimethylfurane as a 'true metabolite' because the quantities detected were always greater before hydrolysis. 3 It has been reported that human and rat n-hexane metabolism follow a similar pattern. Therefore, as a practical application and without increasing either sample or time requirements, the simultaneous quantifi cation of the different metabolites and their excretion profile could provide better information about the metabolic situation of exposed workers than the determi nation of 2, 5-hexanedione alone. According to our experimental results, 4, 5-dihydroxy-2-hexanone itself would be a good toxicity indicator.

Detection of polar stratospheric clouds with ERS-2/GOME data

1995 ◽  
Vol 13 (4) ◽  
pp. 395-405
Author(s):  
R. Meerkoetter
Keyword(s):  
Radiative Transfer ◽  
European Research ◽  
Polar Stratospheric Clouds ◽  
Additional Information ◽  
Tropospheric Aerosol ◽  
Ozone Monitoring ◽  
The Difference ◽  
Stratospheric Clouds

Abstract. Based on radiative transfer calculations, it is studied whether polar stratospheric clouds (PSCs) can be detected by the new Global Ozone Monitoring Experiment (GOME) on board the second European Research Satellite (ERS-2) planned to be launched in 1995. It is proposed to identify PSC-covered areas by use of an indicator, the Normalized Radiance Difference (NRD), which relates the difference of two spectral radiances at 0.515 µm and 0.67 µm to one radiance measured in the centre of the oxygen A-band at 0.76 µm. Simulations are carried out for two solar zenith angles, θ=78.5° and θ=86.2°. They indicate that, in presence of PSCs and with increasing solar zenith angles above θ=80°, the NRD decrease to values clearly below those derived under conditions of a cloud-free stratosphere. Results for θ=86.2° show that the method is successful independent of existing tropospheric clouds, of different tropospheric aerosol loadings, and of surface albedos. Results for θ=78.5° illustrate that PSC detection under conditions of smaller solar zenith angles θ80° needs additional information about tropospheric clouds.

Somatosensory and Auditory Brain Stem Conduction after Head Injury: A Comparison with Clinical Features in Prediction of Outcome

Neurosurgery ◽  
1990 ◽  
Vol 26 (2) ◽  
pp. 278-285 ◽  
Author(s):  
Kenneth Lindsay ◽  
Aydin Pasaoglu ◽  
David Hirst ◽  
Gwen Allardyce ◽  
Ian Kennedy ◽  
...  
Keyword(s):  
Head Injury ◽  
Brain Stem ◽  
Evoked Potential ◽  
Predictive Accuracy ◽  
Normal Subjects ◽  
Prediction Of Outcome ◽  
Prognostic Information ◽  
Additional Information ◽  
Auditory Brain Stem ◽  
The Difference

Abstract Evoked potential conduction times in brain stem auditory (BCT) and central somatosensory pathways (CCT) were recorded from 23 normal subjects and 101 patients with severe head injury. Abnormalities in the CCT and the BCT findings correlated with the clinical indices of brain damage (coma score, motor response, pupil response, and spontaneous and reflex eye movements) in the head-injured patients and each correlated with outcome at 6 months from the injury. The CCT in the “best” hemisphere produced the strongest correlation with outcome (P&lt;0.001). The correlation of the CCT with outcome was stronger in the 47 patients examined 2 to 3 days after the injury (P&lt;0.001) compared to the 34 patients examined within 24 hours after the injury (P&lt;0.02). No such difference was noted for the BCT. Serial studies within the first 2 weeks of injury did not show a consistent pattern and repetition of the investigation over this period did not provide any additional information. We used an INDEP-SELECT discriminant analysis program to determine whether information from the evoked potential data could improve prediction of outcome based on clinical data alone. With the addition of the CCT, the predictive accuracy (expressed as the correct classification probability) increased only slightly from 77 to 80%, and the difference was not significant. We conclude that central somatosensory and auditory brain stem conduction times provide useful prognostic information in paralyzed or sedated patients, but when neurological examination is feasible the benefits of evoked potential analysis do not justify the effort involved in data collection.

Neural network processing of radar scanning data array

2021 ◽  
Author(s):  
V.E. Dmitriyev ◽  
D.V. Popov ◽  
V.A. Shakhnov
Keyword(s):  
Spatial Perception ◽  
Digital Processing ◽  
Radar Data ◽  
Information Value ◽  
Data Array ◽  
Additional Information ◽  
Distribution Of Values ◽  
The Difference ◽  
Radar Data Processing ◽  
Made In

This article deals with the digital processing of a matrix radar image. The information received from the radar scanner needs to be transformed to enable visual perception. The article describes the main methods of digital processing of matrix data, presents the images transformed by them. The aim of the article was the development of a radar data processing algorithm that identifies the contours and edges of examined objects. The authors propose an algorithm for isolating the geometric structure of the scanned area. The difference between the processing method and the known analogues is based on the nature of the change in the values of the array being processed and consists in the double operation of extracting the gradient of the distribution of values. The software implementation of the algorithm is made in C++ using methods from an open library of computer vision. The efficiency of the algorithm was estimated based on comparison with the algorithms for determining edges based on linear filtering and neural networks. The results of the work can be used to create software for mobile short-range radar devices. Imaging from object boundaries and their edges provides spatial perception of the image by the operator, and free areas are available for rendering additional information. This solution allows you to combine scanning devices and thereby increase the information value of the result.

Linguistic cues facilitate children’s understanding of belief-reporting sentences

2021 ◽  
pp. 014272372110486
Author(s):  
Xiaowen Zhang ◽  
Peng Zhou
Keyword(s):  
Gold Medal ◽  
Judgment Task ◽  
False Belief ◽  
Value Judgment ◽  
Additional Information ◽  
Linguistic Cues ◽  
Truth Value ◽  
The Difference ◽  
Underlying Mechanisms ◽  
Mental Verbs

It has been well-documented that although children around 4 years start to attribute false beliefs to others in classic false-belief tasks, they are still less able to evaluate the truth-value of propositional belief-reporting sentences, especially when belief conflicts with reality. This article investigates whether linguistic cues, verb factivity in particular, can facilitate children’s understanding of belief-reporting sentences. Two experiments were implemented, one testing children’s knowledge of verb factivity using a gold medal task, and one investigating children’s interpretation of belief-reporting sentences using a truth-value-judgment task. Both experiments took advantage of the contrast between neutral non-factive mental verbs and strong negatively biased mental verbs. What sets the two apart is that the complement clause following a strong negatively biased mental verb is definitely false, whereas the one following a neutral non-factive mental verb remains indeterminate in the absence of additional information. The findings were that, first, 4-year-old children were able to tell the difference between the two types of mental verbs in factivity, and second, children’s performance was significantly improved when a strong negatively biased mental verb than when a neutral non-factive mental verb was used as the main verb of the belief-reporting sentences. The findings suggest that the use of strong negatively biased mental verbs facilitates children’s understanding of belief-reporting sentences. Implications of the findings are discussed in relation to the underlying mechanisms connecting verb factivity and false-belief understanding.

Exploring the relationship between corporate responsibility and firm performance from a social media perspective

2019 ◽  
Vol 15 (3) ◽  
pp. 296-317 ◽  
Author(s):  
Ray Qing Cao ◽  
Dara G. Schniederjans ◽  
Vicky Ching Gu ◽  
Marc J. Schniederjans
Keyword(s):  
Social Media ◽  
Corporate Responsibility ◽  
Abnormal Return ◽  
Media Framing ◽  
Idiosyncratic Risk ◽  
Daily Basis ◽  
Expected Return ◽  
Content Type ◽  
The Difference ◽  
The Relationship

Purpose Corporate responsibility perceptions from stakeholders are becoming more difficult to manage. This is in part because of large amount of social media being projected to stakeholders on a daily basis. In light of this, the purpose of this paper is to examine the relationship between corporate responsibility framing from the social media perspective firm’s performance as defined by abnormal-return (defined as the difference between a single stock or portfolios return and the expected return) and idiosyncratic-risk (defined as the risk of a particular investment because of firm-specific characteristics). Design/methodology/approach Hypotheses are developed through agenda-setting theory and stakeholder and shareholder viewpoints. The research model is tested using sentiment analysis from a collection of social media from several industries. Findings The results provide support that three corporate responsibility social media categories (economic, social and environmental-framing) will have different impacts (delayed, immediate) on abnormal-return and idiosyncratic-risk. This study finds differences between immediate (one-day lag) and delayed (three-day lag) associations on abnormal-return and idiosyncratic-risk. Originality/value This study also suggests differences between the amount and sentiment of corporate responsibility social media framing on abnormal-return and idiosyncratic-risk. Finally, results identify interaction effects between different corporate responsibility social media categories.

scholarly journals Value-at-risk modeling and forecasting with range-based volatility models: empirical evidence

2017 ◽  
Vol 28 (75) ◽  
pp. 361-376 ◽  
Author(s):  
Leandro dos Santos Maciel ◽  
Rosangela Ballini
Keyword(s):  
At Risk ◽  
Value At Risk ◽  
Garch Models ◽  
Time Interval ◽  
Risk Modeling ◽  
Additional Information ◽  
Volatility Models ◽  
Modeling And Forecasting ◽  
The Difference ◽  
Market Indexes

ABSTRACT This article considers range-based volatility modeling for identifying and forecasting conditional volatility models based on returns. It suggests the inclusion of range measuring, defined as the difference between the maximum and minimum price of an asset within a time interval, as an exogenous variable in generalized autoregressive conditional heteroscedasticity (GARCH) models. The motivation is evaluating whether range provides additional information to the volatility process (intraday variability) and improves forecasting, when compared to GARCH-type approaches and the conditional autoregressive range (CARR) model. The empirical analysis uses data from the main stock market indexes for the U.S. and Brazilian economies, i.e. S&P 500 and IBOVESPA, respectively, within the period from January 2004 to December 2014. Performance is compared in terms of accuracy, by means of value-at-risk (VaR) modeling and forecasting. The out-of-sample results indicate that range-based volatility models provide more accurate VaR forecasts than GARCH models.

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