SU-E-T-37: Evaluation of Software Systems That Estimate Patient Dose Errors Based on Planar IMRT QA Measurements

2012 ◽  
Vol 39 (6Part10) ◽  
pp. 3710-3711 ◽  
Author(s):  
M Bakhtiari ◽  
A Parniani ◽  
F Lerma ◽  
S Reynolds ◽  
J Jordan ◽  
...  
Keyword(s):  
Patient Dose ◽  
Software Systems ◽  
Imrt Qa ◽  
Dose Errors

scholarly journals Per-beam, planar IMRT QA passing rates do not predict clinically relevant patient dose errors

2011 ◽  
Vol 38 (2) ◽  
pp. 1037-1044 ◽  
Author(s):  
Benjamin E. Nelms ◽  
Heming Zhen ◽  
Wolfgang A. Tomé
Keyword(s):  
Patient Dose ◽  
Imrt Qa ◽  
Passing Rates ◽  
Dose Errors

SU-E-T-405: Evaluation of IMRT QA Using 3DVH, a 3D Patient Dose and Verification Analysis Software

2011 ◽  
Vol 38 (6Part16) ◽  
pp. 3581-3581 ◽  
Author(s):  
G Jarry ◽  
D Martin ◽  
M Lemire ◽  
M Ayles ◽  
P Pater
Keyword(s):  
Patient Dose ◽  
Analysis Software ◽  
Imrt Qa

Evaluation of Current IMRT QA versus Dose Errors in Clinically Relevant Areas

2011 ◽  
Vol 81 (2) ◽  
pp. S829
Author(s):  
D. Gasic ◽  
H. Benedek ◽  
M. Enmark ◽  
T. Knöös
Keyword(s):  
Imrt Qa ◽  
Dose Errors

SU-GG-T-195: On the Correlation of Conventional IMRT QA Metrics to Clinical Impact in Per-Patient Dose QA

2010 ◽  
Vol 37 (6Part18) ◽  
pp. 3229-3230 ◽  
Author(s):  
H Zhen ◽  
B Nelms ◽  
W Tome
Keyword(s):  
Clinical Impact ◽  
Patient Dose ◽  
Imrt Qa

scholarly journals A Varian DynaLog file‐based procedure for patient dose‐volume histogram‐based IMRT QA

2014 ◽  
Vol 15 (2) ◽  
pp. 100-109 ◽  
Author(s):  
Juan F. Calvo‐Ortega ◽  
Tony Teke ◽  
Sandra Moragues ◽  
Miquel Pozo ◽  
Joan Casals
Keyword(s):  
Patient Dose ◽  
Dose Volume Histogram ◽  
Imrt Qa ◽  
Dose Volume

Methods of parallel computing for multilevel fuzzy Takagi – Sugeno systems

2016 ◽  
pp. 141-149
Author(s):  
S.V. Yershov ◽  
◽  
R.М. Ponomarenko ◽  
Keyword(s):  
Dynamic Models ◽  
Fuzzy Inference ◽  
Knowledge Bases ◽  
Comparative Characteristic ◽  
Software Systems ◽  
Scientific Papers ◽  
Speed Up ◽  
Diagnostic Software ◽  
Takagi Sugeno

Parallel tiered and dynamic models of the fuzzy inference in expert-diagnostic software systems are considered, which knowledge bases are based on fuzzy rules. Tiered parallel and dynamic fuzzy inference procedures are developed that allow speed up of computations in the software system for evaluating the quality of scientific papers. Evaluations of the effectiveness of parallel tiered and dynamic schemes of computations are constructed with complex dependency graph between blocks of fuzzy Takagi – Sugeno rules. Comparative characteristic of the efficacy of parallel-stacked and dynamic models is carried out.

A Literature Review Study of Software Defect Prediction using Machine Learning Techniques

2018 ◽  
Vol 6 (6) ◽  
pp. 300 ◽  
Author(s):  
Feidu Akmel ◽  
Ermiyas Birihanu ◽  
Bahir Siraj
Keyword(s):  
Machine Learning ◽  
Software Metrics ◽  
Quality Standard ◽  
Machine Learning Techniques ◽  
Software Systems ◽  
Health Care Insurance ◽  
Software Defect ◽  
Learning Techniques ◽  
Software Product

Software systems are any software product or applications that support business domains such as Manufacturing,Aviation, Health care, insurance and so on.Software quality is a means of measuring how software is designed and how well the software conforms to that design. Some of the variables that we are looking for software quality are Correctness, Product quality, Scalability, Completeness and Absence of bugs, However the quality standard that was used from one organization is different from other for this reason it is better to apply the software metrics to measure the quality of software. Attributes that we gathered from source code through software metrics can be an input for software defect predictor. Software defect are an error that are introduced by software developer and stakeholders. Finally, in this study we discovered the application of machine learning on software defect that we gathered from the previous research works.

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