The Experts below are selected from a list of 927 Experts worldwide ranked by ideXlab platform
C H Clark - One of the best experts on this subject based on the ideXlab platform.
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the use of Log File Analysis within vmat audits
British Journal of Radiology, 2016Co-Authors: Conor K Mcgarry, Christina E Agnew, M Hussein, Yatman Tsang, Alan R Hounsell, C H ClarkAbstract:Objective:This work investigated the delivery accuracy of different Varian linear accelerator models using Log File-derived multileaf collimator (MLC) root mean square (RMS) values.Methods:Seven centres independently created a plan on the same virtual phantom using their own planning system, and the Log Files were analyzed following delivery of the plan in each centre to assess MLC positioning accuracy. A single standard plan was also delivered by the seven centres to remove variations in complexity, and the Log Files were analyzed for Varian TrueBeams and Clinacs (2300IX or 2100CD models).Results:Varian TrueBeam accelerators had better MLC positioning accuracy (<1.0 mm) than the 2300IX (<2.5 mm) following delivery of the plans created by each centre and also the standard plan. In one case, Log Files provided evidence that reduced delivery accuracy was not associated with the linear accelerator model but was due to planning issues.Conclusion:Log Files are useful in identifying differences between linear a...
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The use of Log File Analysis within VMAT audits
British Journal of Radiology, 2016Co-Authors: Conor K Mcgarry, Christina E Agnew, M Hussein, Yatman Tsang, Alan R Hounsell, C H ClarkAbstract:Objective:This work investigated the delivery accuracy of different Varian linear accelerator models using Log File-derived multileaf collimator (MLC) root mean square (RMS) values.Methods:Seven centres independently created a plan on the same virtual phantom using their own planning system, and the Log Files were analyzed following delivery of the plan in each centre to assess MLC positioning accuracy. A single standard plan was also delivered by the seven centres to remove variations in complexity, and the Log Files were analyzed for Varian TrueBeams and Clinacs (2300IX or 2100CD models).Results:Varian TrueBeam accelerators had better MLC positioning accuracy (
Thomas Berkel - One of the best experts on this subject based on the ideXlab platform.
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a new direction for Log File Analysis in cscl experiences with a spatio temporal metric
Computer Supported Collaborative Learning, 2005Co-Authors: Till Schummer, Janwillem Strijbos, Thomas BerkelAbstract:This paper discusses the importance and difficulties of assessing interaction between students. To ease the detection of interaction in student groups, a metric is developed that can measure the level of interaction based on Log File data. The metric is based on a spatial model and detects actions that take place in close spatial or temporal proximity. After providing a formal definition of the metric, an exploratory Analysis of interaction in two different settings is reported to determine the feasibility of the measure: synchronous interaction in a collaborative puzzle game and asynchronous interaction in student groups that use the BSCW shared workspace system.
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CSCL - A new direction for Log File Analysis in CSCL: experiences with a spatio-temporal metric
Proceedings of the 2005 conference on Computer support for collaborative learning learning 2005: the next 10 years! - CSCL '05, 2005Co-Authors: Till Schummer, Janwillem Strijbos, Thomas BerkelAbstract:This paper discusses the importance and difficulties of assessing interaction between students. To ease the detection of interaction in student groups, a metric is developed that can measure the level of interaction based on Log File data. The metric is based on a spatial model and detects actions that take place in close spatial or temporal proximity. After providing a formal definition of the metric, an exploratory Analysis of interaction in two different settings is reported to determine the feasibility of the measure: synchronous interaction in a collaborative puzzle game and asynchronous interaction in student groups that use the BSCW shared workspace system.
J. H. Andrews - One of the best experts on this subject based on the ideXlab platform.
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General test result checking with Log File Analysis
IEEE Transactions on Software Engineering, 2003Co-Authors: J. H. Andrews, Yingjun ZhangAbstract:We describe and apply a lightweight formal method for checking test results. The method assumes that the software under test writes a text Log File; this Log File is then analyzed by a program to see if it reveals failures. We suggest a state-machine-based formalism for specifying the Log File analyzer programs and describe a language and implementation based on that formalism. We report on empirical studies of the application of Log File Analysis to random testing of units. We describe the results of experiments done to compare the performance and effectiveness of random unit testing with coverage checking and Log File Analysis to other unit testing procedures. The experiments suggest that writing a formal Log File analyzer and using random testing is competitive with other formal and informal methods for unit testing.
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Broad-spectrum studies of Log File Analysis
Proceedings of the 2000 International Conference on Software Engineering. ICSE 2000 the New Millennium, 2000Co-Authors: J. H. Andrews, Yingjun ZhangAbstract:This paper reports on research into applying the technique of Log File Analysis for checking test results to a broad range of testing and other tasks. The studies undertaken included applying Log File Analysis to both unit- and system-level testing and to requirements of both safety-critical and non-critical systems, and the use of Log File Analysis in combination with other testing methods. The paper also reports on the technique of using Log File analyzers to simulate the software under test, both in order to validate the analyzers and to clarify requirements. It also discusses practical issues to do with the completeness of the approach, and includes comparisons to other recently-published approaches to Log File Analysis.
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Testing using Log File Analysis: tools, methods, and issues
Proceedings 13th IEEE International Conference on Automated Software Engineering (Cat. No.98EX239), 1998Co-Authors: J. H. AndrewsAbstract:Large software systems often keep Log Files of events. Such Log Files can be analyzed to check whether a run of a program reveals faults in the system. We discuss how such Log Files can be used in software testing. We present a framework for automatically analyzing Log Files, and describe a language for specifying analyzer programs and an implementation of that language. The language permits compositional, compact specifications of software, which act as test oracles; we discuss the use and efficacy of these oracles for unit- and system-level testing in various settings. We explore methodoLogical issues such as efficiency and Logging policies, and the scope and limitations of the framework. We conclude that testing using Log File Analysis constitutes a useful methodoLogy for software verification, somewhere between current testing practice and formal verification methodoLogies
Till Schummer - One of the best experts on this subject based on the ideXlab platform.
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a new direction for Log File Analysis in cscl experiences with a spatio temporal metric
Computer Supported Collaborative Learning, 2005Co-Authors: Till Schummer, Janwillem Strijbos, Thomas BerkelAbstract:This paper discusses the importance and difficulties of assessing interaction between students. To ease the detection of interaction in student groups, a metric is developed that can measure the level of interaction based on Log File data. The metric is based on a spatial model and detects actions that take place in close spatial or temporal proximity. After providing a formal definition of the metric, an exploratory Analysis of interaction in two different settings is reported to determine the feasibility of the measure: synchronous interaction in a collaborative puzzle game and asynchronous interaction in student groups that use the BSCW shared workspace system.
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CSCL - A new direction for Log File Analysis in CSCL: experiences with a spatio-temporal metric
Proceedings of the 2005 conference on Computer support for collaborative learning learning 2005: the next 10 years! - CSCL '05, 2005Co-Authors: Till Schummer, Janwillem Strijbos, Thomas BerkelAbstract:This paper discusses the importance and difficulties of assessing interaction between students. To ease the detection of interaction in student groups, a metric is developed that can measure the level of interaction based on Log File data. The metric is based on a spatial model and detects actions that take place in close spatial or temporal proximity. After providing a formal definition of the metric, an exploratory Analysis of interaction in two different settings is reported to determine the feasibility of the measure: synchronous interaction in a collaborative puzzle game and asynchronous interaction in student groups that use the BSCW shared workspace system.
Timothy R Huerta - One of the best experts on this subject based on the ideXlab platform.
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metrics for outpatient portal use based on Log File Analysis algorithm development
Journal of Medical Internet Research, 2020Co-Authors: Gennaro Di Tosto, Ann Scheck Mcalearney, Naleef Fareed, Timothy R HuertaAbstract:BACKGROUND Web-based outpatient portals help patients engage in the management of their health by allowing them to access their medical information, schedule appointments, track their medications, and communicate with their physicians and care team members. Initial studies have shown that portal adoption positively affects health outcomes; however, early studies typically relied on survey data. Using data from health portal applications, we conducted systematic assessments of patients' use of an outpatient portal to examine how patients engage with the tool. OBJECTIVE This study aimed to document the functionality of an outpatient portal in the context of outpatient care by mining portal usage data and to provide insights into how patients use this tool. METHODS Using audit Log Files from the outpatient portal associated with the electronic health record system implemented at a large multihospital academic medical center, we investigated the behavioral traces of a study population of 2607 patients who used the portal between July 2015 and February 2019. Patient portal use was defined as having an active account and having accessed any portal function more than once during the study time frame. RESULTS Through our Analysis of audit Log File data of the number and type of user interactions, we developed a taxonomy of functions and actions and computed analytic metrics, including frequency and comprehensiveness of use. We additionally documented the computational steps required to diagnose artifactual data and arrive at valid usage metrics. Of the 2607 patients in our sample, 2511 were active users of the patients portal where the median number of sessions was 94 (IQR 207). Function use was comprehensive at the patient level, while each session was instead limited to the use of one specific function. Only 17.45% (78,787/451,762) of the sessions were linked to activities involving more than one portal function. CONCLUSIONS In discussing the full methodoLogical choices made in our Analysis, we hope to promote the replicability of our study at other institutions and contribute to the establishment of best practices that can facilitate the adoption of behavioral metrics that enable the measurement of patient engagement based on the outpatient portal use.
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Metrics for Outpatient Portal Use Based on Log File Analysis: Algorithm Development (Preprint)
2019Co-Authors: Gennaro Di Tosto, Ann Scheck Mcalearney, Naleef Fareed, Timothy R HuertaAbstract:BACKGROUND Web-based outpatient portals help patients engage in the management of their health by allowing them to access their medical information, schedule appointments, track their medications, and communicate with their physicians and care team members. Initial studies have shown that portal adoption positively affects health outcomes; however, early studies typically relied on survey data. Using data from health portal applications, we conducted systematic assessments of patients’ use of an outpatient portal to examine how patients engage with the tool. OBJECTIVE This study aimed to document the functionality of an outpatient portal in the context of outpatient care by mining portal usage data and to provide insights into how patients use this tool. METHODS Using audit Log Files from the outpatient portal associated with the electronic health record system implemented at a large multihospital academic medical center, we investigated the behavioral traces of a study population of 2607 patients who used the portal between July 2015 and February 2019. Patient portal use was defined as having an active account and having accessed any portal function more than once during the study time frame. RESULTS Through our Analysis of audit Log File data of the number and type of user interactions, we developed a taxonomy of functions and actions and computed analytic metrics, including frequency and comprehensiveness of use. We additionally documented the computational steps required to diagnose artifactual data and arrive at valid usage metrics. Of the 2607 patients in our sample, 2511 were active users of the patients portal where the median number of sessions was 94 (IQR 207). Function use was comprehensive at the patient level, while each session was instead limited to the use of one specific function. Only 17.45% (78,787/451,762) of the sessions were linked to activities involving more than one portal function. CONCLUSIONS In discussing the full methodoLogical choices made in our Analysis, we hope to promote the replicability of our study at other institutions and contribute to the establishment of best practices that can facilitate the adoption of behavioral metrics that enable the measurement of patient engagement based on the outpatient portal use.
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patient engagement as measured by inpatient portal use methodoLogy for Log File Analysis
Journal of Medical Internet Research, 2018Co-Authors: Timothy R Huerta, Naleef Fareed, Jennifer L Hefner, Cynthia J Sieck, Christine M Swoboda, Ronald L Taylor, Ann Scheck McalearneyAbstract:BACKGROUND: Inpatient portals (IPPs) have the potential to increase patient engagement and satisfaction with their health care. An IPP provides a hospitalized patient with similar functions to those found in outpatient portals, including the ability to view vital signs, laboratory results, and medication information; schedule appointments; and communicate with their providers. However, IPPs may offer additional functions such as meal planning, real-time messaging with the inpatient care team, daily schedules, and access to educational materials relevant to their specific condition. In practice, IPPs have been developed as websites and tablet apps, with hospitals providing the required technoLogy as a component of care during the patient's stay. OBJECTIVE: This study aimed to describe how inpatients are using IPPs at the first academic medical center to implement a system-wide IPP and document the challenges and choices associated with this analytic process. METHODS: We analyzed the audit Log Files of IPP users hospitalized between January 2014 and January 2016. Data regarding the date/time and duration of interactions with each of the MyChart Bedside modules (eg, view lab results or medications and patient schedule) and activities (eg, messaging the provider and viewing educational videos) were captured as part of the system audit Logs. The development of a construct to describe the length of time associated with a single coherent use of the tool-which we call a session-provides a foundational unit of Analysis. We defined frequency as the number of sessions a patient has during a given provision day. We defined comprehensiveness in terms of the percentage of functions that an individual uses during a given provision day. RESULTS: The analytic process presented data challenges such as length of stay and tablet-provisioning factors. This study presents data visualizations to illustrate a series of data-cleaning issues. In the presence of these robust approaches to data cleaning, we present the baseline usage patterns associated with our patient panel. In addition to frequency and comprehensiveness, we present considerations of median data to mitigate the effect of outliers. CONCLUSIONS: Although other studies have published usage data associated with IPPs, most have not explicated the challenges and choices associated with the analytic approach deployed within each study. Our intent in this study was to be somewhat exhaustive in this area, in part, because replicability requires common metrics. Our hope is that future researchers in this area will avail themselves of these perspectives to engage in critical assessment moving forward.
