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Test Set Optimization by Machine Learning Algorithms
[article]
2020
arXiv
pre-print
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Diagnosis results are highly dependent on the volume of test set. ...
Numerical results show that SVM reaches a diagnosis accuracy of 90.4% while deducting the volume of test set by 35.24%. ...
In this paper, the diagnosis process has been optimized by reducing the test volume. ...
arXiv:2010.15240v1
fatcat:nrfaypuqcbf5nl3ejkegcafcga
Evaluating combinations of diagnostic tests to discriminate different dementia types
2018
Alzheimer's and Dementia: Diagnosis, Assessment and Disease Monitoring
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We studied, using a data-driven approach, how different combinations of diagnostic tests contribute to the differential diagnosis of dementia. ...
We used a classifier to assess accuracy for individual performance and combinations of cognitive tests, cerebrospinal fluid biomarkers, and automated magnetic resonance imaging features for pairwise differentiation ...
The optimized combinations of diagnostic tests for comparison of AD vs. VaD and AD vs. ...
doi:10.1016/j.dadm.2018.07.003
pmid:30320203
pmcid:PMC6180596
fatcat:qnnijbytlrggnpm6iqxg5rlxs4
Improving the Accuracy of Early Diagnosis of Thyroid Nodule Type Based on the SCAD Method
2016
Asian Pacific Journal of Cancer Prevention
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Although early diagnosis of thyroid nodule type is very important, the diagnostic accuracy of standard tests is a challenging issue. ...
In addition to maximum diameters of nodules and lobes, their volumes were considered as related factors for malignancy prediction (a total of 16 factors). ...
The authors are thankful to the Trauma Research Center staff for their assistance in data gathering and Dr. HR. Abbasi for his collaboration in cancer diagnosis. ...
doi:10.7314/apjcp.2016.17.4.1861
fatcat:vdtnyrzacja3xo677tu2xgbeee
Impact of Sensor Data Characterization with Directional Nature of Fault and Statistical Feature Combination for Defect Detection on Roll-to-Roll Printed Electronics
2021
Sensors
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To improve the diagnosis performances, optimal sensor selection with Sensor Data Efficiency Evaluation, sensitivity evaluation for axis selection with Directional Nature of Fault and feature variable optimization ...
Data acquisition with three triaxial acceleration sensors for fault diagnosis of four major defects such as doctor blade tilting fault was obtained. ...
Data Availability Statement: Not applicable.
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/s21248454
pmid:34960547
pmcid:PMC8706900
fatcat:lzgiklr4pbaablofwkvjiywduy
A Power Transformer Fault Diagnosis Method-based Hybrid Improved Seagull Optimization Algorithm and Support Vector Machine
2021
IEEE Access
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In addition, TISOA is further proposed to optimize the SVM parameters to build the optimal diagnosis model based on SVM. For the SOA, three improvement methods are proposed. ...
Therefore, a research idea is provided for solving practical engineering problems in the field of fault diagnosis. ...
Diagnosis results of four methods.
TABLE 2 . 2 The benchmark functions test results.
TABLE 3 . 3 CEC2015 test results. VOLUME 10, 2022
TABLE 4 . 4 Fault data. ...
doi:10.1109/access.2021.3127164
fatcat:i2rzmbv3nbgunfcq7xr2eficxq
A novel rotating machinery fault diagnosis method based on adaptive deep belief network structure and dynamic learning rate under variable working conditions
2021
IEEE Access
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However, due to the problems of gradient 2 VOLUME 4, 2016 ...
INDEX TERMS Deep belief network,Particle swarm optimization,Dynamic learning rate strategy,Multi condition fault diagnosis,Wavelet packet energy entropy Recently,many feature extraction methods were proposed ...
So it can be concluded that this method has a good diagnosis effect for test sample data. ...
doi:10.1109/access.2021.3066594
fatcat:i3rf3bohbzbrredcsnhstaluhe
Optimized Reconstruction Algorithm-Processed CT Image in the Diagnosis of Correlation between Epicardial Fat Volume and Coronary Heart Disease
2022
Scientific Programming
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Then, the optimized algorithm was applied to the image reconstruction of multislice spiral CT image data after testing its sensitivity, accuracy, and specificity. 60 patients with suspected angina pectoris ...
An optimized reconstruction algorithm was constructed based on compressed sensing theory in this study. ...
Measurement data were expressed as mean-± standard deviation (x ± s), and count data were expressed as a percentage. e t test and χ2 test were performed. e pathological group and the normal group were ...
doi:10.1155/2022/2883175
fatcat:7qh6guxesrbdhhxqnw5qnrbwz4
Combination of Culture, Antigen and Toxin Detection, and Cytotoxin Neutralization Assay for OptimalClostridium difficileDiagnostic Testing
2013
Canadian Journal of Infectious Diseases and Medical Microbiology
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optimal diagnosis ofC difficileinfection. ...
Following the algorithm, culture was needed for only 2.72% of all specimens submitted forC difficiletesting.CONCLUSION: The overview of the data illustrated the significance of each stage of this four-stepC ...
Analysis of one year of data supports the value of this four-step algorithm as the optimal approach to diagnosis of CDI. ...
doi:10.1155/2013/934945
pmid:24421808
pmcid:PMC3720004
fatcat:r5r7746wfngkpkfq7aigxrrdoe
A Fault Diagnosis Model of Power Transformers Based on Dissolved Gas Analysis Features Selection and Improved Krill Herd Algorithm Optimized Support Vector Machine
2019
IEEE Access
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edge data in the fuzzy area; 2) the SVM parameters and 11 features are encoded by a binary code technique; 3) a preferred DGA feature set for fault diagnosis of power transformers is selected by genetic ...
The following work has been done in this paper: 1) IEC TC 10 fault data and other 117 sets of fault data in China are preprocessed in order to reduce the influence on the diagnosis results causing by the ...
Fault diagnosis results.
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doi:10.1109/access.2019.2927018
fatcat:xf4mnukrwza7vdbyz5ykloz3bi
Using Artificial Intelligence and Big Data-Based Documents to Optimize Medical Coding
[chapter]
2019
Artificial Intelligence - Applications in Medicine and Biology [Working Title]
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It is increasingly difficult to manage large volumes of data in a specific clinical context such as quality coding of medical services. ...
Clinical information systems (CISs) in some hospitals streamline the data management from data warehouses. ...
The volume of data received by one node for the test is 1.6 million documents representing 1 year of the hospital stays. The volume of documents can be worm at 40 times the initial volume. ...
doi:10.5772/intechopen.85749
fatcat:wuu4leey4zcwraa4pxsd7zvcb4
A data-mining approach to improving Polycythemia Vera diagnosis
2002
Computers & industrial engineering
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This paper presents a data-mining approach to the extraction of new decision rules for Polycythemia Vera (PV) diagnosis, based on a reduced and optimized set of lab parameters. ...
New rules for improved differential diagnosis of PV are specified based on these four parameters. ...
group criteria PVSG for diagnosis of PV Lab tests Category A Category B A1: Total RBC volume (REDMAS), B1: Thrombocytosis (WBC) . 400,000 mm 23 Male $ 36 ml/kg BW, Female $ 32 ml/kg BW A2: Arterial saturation ...
doi:10.1016/s0360-8352(02)00138-9
fatcat:hxawedlah5f3hahewbdf2gul6m
Fault Diagnosis of Motor Bearings Based on a Convolutional Long Short-Term Memory Network of Bayesian Optimization
2021
IEEE Access
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Then, the most accurate model is saved for subsequent bearing fault diagnosis performance testing. ...
The optimized hyperparameter training model is saved for later motor bearing vibration signal fault diagnosis. Step 4: Fault classification. ...
doi:10.1109/access.2021.3093363
fatcat:wmtu22j5ivewjggpoqjvap2dxe
Classifying Transformer Winding Deformation Fault Types and Degrees using FRA based on Support Vector Machine
2019
IEEE Access
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Frequency response analysis (FRA) has been widely accepted as an effective tool for winding deformation fault diagnosis, which is one of the common failures for power transformers. ...
Furthermore, advanced optimization algorithms are also applied to improve the performance of models. ...
For more information, see http://creativecommons.org/licenses/by/4.0/ VOLUME 7, 2019
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doi:10.1109/access.2019.2932497
fatcat:tdpdqvlc7jd5vox4klq4mluz7y
Embedding infrastructure IP for SOC yield improvement
2002
Proceedings 2002 Design Automation Conference (IEEE Cat. No.02CH37324)
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It also describes several examples of such embedded IPs for detection, analysis and correction. ...
The key alternative is gathering failure data by using embedded diagnosis I-IP, such as signature analyzers, dedicated test vehicles or on-chip test processors, and then analyzing the obtained data by ...
Figure (5) Diagnosis for Logic Blocks (Source: LogicVision) In the case of random logic blocks, the embedded test and diagnosis IP is comprised of scan chains and test points incorporated into the random ...
doi:10.1109/dac.2002.1012716
fatcat:5xs46ofyjjglvazfmpbjf2viey
Embedding infrastructure IP for SOC yield improvement
2002
Proceedings - Design Automation Conference
Preserved Fulltext
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It also describes several examples of such embedded IPs for detection, analysis and correction. ...
The key alternative is gathering failure data by using embedded diagnosis I-IP, such as signature analyzers, dedicated test vehicles or on-chip test processors, and then analyzing the obtained data by ...
Figure (5) Diagnosis for Logic Blocks (Source: LogicVision) In the case of random logic blocks, the embedded test and diagnosis IP is comprised of scan chains and test points incorporated into the random ...
doi:10.1145/514097.514098
fatcat:xcob5z2vynfglofukdz2i6xwim
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