MO‐D‐213‐08: Remote Dosimetric Credentialing for Clinical Trials with the Virtual EPID Standard Phantom Audit (VESPA)

Lehmann, Jöerg; Miri, Narges; Vial, P; Hatton, Joan; Zwan, Benjamin; Craig, A.M.; Beenstock, Victoria; Molloy, T; Sloan, Kenneth R.; Greer, Peter

doi:10.1118/1.4925324

Cited by 2 publications

(2 citation statements)

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“…Ratcliffe et al and others in the process of knowledge discovery, combine rough set and fuzzy set theory [13]. Lehmann et al constructed fuzzy system identification methods and fuzzy system knowledge models and constructed an intelligent expert system [14]. When Aitken studied the data acquisition of financial websites, same as general data capture, through the XMLHTTP object provided by Microsoft, get the overall data of financial webpages.…”

Section: Literature Reviewmentioning

confidence: 99%

Data Mining Optimization Software and Its Application in Financial Audit Data Analysis

Shan

Xiao

Che

et al. 2022

Mobile Information Systems

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The scope of finance is very wide, data also plays a very important role in the financial industry, a small data change, and it may have a great impact on the economy. Therefore, the author proposes data mining optimization software and its application in financial audit data analysis. First, discuss the decision tree method, the main function module design of the system software, the financial analysis software method of weighted multiple random decision trees is described. To conduct verification experiments, the decision-making effect of constructing 10 random decision trees is the best. So, the author constructed a total of 10 random decision trees to analyze the data, since the tree is constructed using a random method, in order to verify the stability of decision tree classification, a total of 5 experiments were carried out, the training data set for each experiment, randomly select 1200 pieces of data from the original data set as training data, the tree is constructed by randomly selecting 12 attributes from 24 attributes. The remaining 300 pieces of data are used as verification data. As can be seen from the results, the accuracy of the random decision tree method is about 10% higher than that of C4.5. In order to improve the accuracy rate of high risk, 300 pieces of high-risk data were added to the training data set. To change the original random sampling into stratified sampling, according to the high, medium, and low risk, the original data is stratified; random sampling is used for each layer, thereby ensuring the amount of training data with high risk. The accuracy of decision tree classification is related to the number of samples of the training data, the larger the number of samples, the more accurate the classification of the constructed decision tree.

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Section: Literature Reviewmentioning

confidence: 99%

Data Mining Optimization Software and Its Application in Financial Audit Data Analysis

Shan

Xiao

Che

et al. 2022

Mobile Information Systems

View full text Add to dashboard Cite

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“…A recent development is the implementation of an EPID based dosimetry audit (Lehmann et al 2015). Here the instructions and CT data sets required for planning are available on the website of the clinical trials group.…”

Section: Auditingmentioning

confidence: 99%

Dosimetry of ionising radiation in modern radiation oncology

2016

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Dosimetry of ionising radiation is a well-established and mature branch of physical sciences with many applications in medicine and biology. In particular radiotherapy relies on dosimetry for optimisation of cancer treatment and avoidance of severe toxicity for patients. Several novel developments in radiotherapy have introduced new challenges for dosimetry with small and dynamically changing radiation fields being central to many of these applications such as stereotactic ablative body radiotherapy and intensity modulated radiation therapy. There is also an increasing awareness of low doses given to structures not in the target region and the associated risk of secondary cancer induction. Here accurate dosimetry is important not only for treatment optimisation but also for the generation of data that can inform radiation protection approaches in the future. The article introduces some of the challenges and highlights the interdependence of dosimetric calculations and measurements. Dosimetric concepts are explored in the context of six application fields: reference dosimetry, small fields, low dose out of field, in vivo dosimetry, brachytherapy and auditing of radiotherapy practice. Recent developments of dosimeters that can be used for these purposes are discussed using spatial resolution and number of dimensions for measurement as sorting criteria. While dosimetry is ever evolving to address the needs of advancing applications of radiation in medicine two fundamental issues remain: the accuracy of the measurement from a scientific perspective and the importance to link the measurement to a clinically relevant question. This review aims to provide an update on both of these.

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MO‐D‐213‐08: Remote Dosimetric Credentialing for Clinical Trials with the Virtual EPID Standard Phantom Audit (VESPA)

Cited by 2 publications

References 0 publications

Data Mining Optimization Software and Its Application in Financial Audit Data Analysis

Data Mining Optimization Software and Its Application in Financial Audit Data Analysis

Dosimetry of ionising radiation in modern radiation oncology

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