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Test Set Optimization by Machine Learning Algorithms [article]

Kaiming Fu and Yulu Jin and Zhousheng Chen
2020 arXiv   pre-print
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

Marie Bruun, Hanneke F.M. Rhodius-Meester, Juha Koikkalainen, Marta Baroni, Le Gjerum, Afina W. Lemstra, Frederik Barkhof, Anne M. Remes, Timo Urhemaa, Antti Tolonen, Daniel Rueckert, Mark van Gils (+8 others)
2018 Alzheimer's and Dementia: Diagnosis, Assessment and Disease Monitoring  
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

Hadi Raeisi Shahraki, Saeedeh Pourahmad, Shahram Paydar, Mohsen Azad
2016 Asian Pacific Journal of Cancer Prevention  
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

Yoonjae Lee, Minho Jo, Gyoujin Cho, Changbeom Joo, Changwoo Lee
2021 Sensors  
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

Yuhan Wu, Xianbo Sun, Yi Zhang, Xianjing Zhong, Lei Cheng
2021 IEEE Access  
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

Peiming Shi, Peng Xue, Aoyun Liu, Dongying Han
2021 IEEE Access  
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

Enzhong Xue, Qiangqiang Jing, M Pallikonda Rajasekaran
2022 Scientific Programming  
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

Michelle J Alfa, Shadi Sepehri
2013 Canadian Journal of Infectious Diseases and Medical Microbiology  
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

Yiyi Zhang, Xin Li, Hanbo Zheng, Huilu Yao, Jiefeng Liu, Chaohai Zhang, Hongbo Peng, Jian Jiao
2019 IEEE Access  
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. VOLUME 7, 2019 VOLUME 7, 2019 VOLUME 7, 2019 VOLUME 7, 2019 VOLUME 7, 2019  ... 
doi:10.1109/access.2019.2927018 fatcat:xf4mnukrwza7vdbyz5ykloz3bi

Using Artificial Intelligence and Big Data-Based Documents to Optimize Medical Coding [chapter]

Joseph Noussa-Yao, Didier Heudes, Patrice Degoulet
2019 Artificial Intelligence - Applications in Medicine and Biology [Working Title]  
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

Mehmed Kantardzic, Benjamin Djulbegovic, Hazem Hamdan
2002 Computers & industrial engineering  
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

Zhen Li, Yang Wang, Jianeng Ma
2021 IEEE Access  
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

Jiangnan Liu, Zhongyong Zhao, Chao Tang, Chenguo Yao, Chengxiang Li, Syed Islam
2019 IEEE Access  
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 VOLUME 7, 2019 VOLUME 7, 2019 VOLUME 7, 2019 VOLUME 7, 2019 VOLUME  ... 
doi:10.1109/access.2019.2932497 fatcat:tdpdqvlc7jd5vox4klq4mluz7y

Embedding infrastructure IP for SOC yield improvement

Y. Zorian
2002 Proceedings 2002 Design Automation Conference (IEEE Cat. No.02CH37324)  
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

Yervant Zorian
2002 Proceedings - Design Automation Conference  
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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