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Detection and Classification of Melanoma Skin Cancer Using Image Processing Technique
Published 2023-10-01“…The SVM classifier achieved an 86.6% classification accuracy, while the CNN maintained a 91% accuracy rate after 100 compute epochs. …”
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Classification and visual explanation for COVID-19 pneumonia from CT images using triple learning
Published 2022-12-01Get full text
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Classification of cirrhotic patients with or without minimal hepatic encephalopathy and healthy subjects using resting-state attention-related network analysis.
Published 2014-01-01“…With FC strength of ROIs from three networks as indicators, LDA yielded 94.6% classification accuracy between MHE and HC (100% sensitivity and 88.2% specificity) and 85.4% classification accuracy between MHE and NMHE (90.0% sensitivity and 81.0% specificity). …”
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Geographic Information System For The Mapping Of Value Land Zone Of District Bengkong Based On AHP Analysis
Published 2017-07-01“…The result of the research in the form of web map VLZ with 6 classification of land price, the prices that Bengkong area concertrated settlement areas as Rp 3.500.000/sqm for the land prices are the highest in the village of Sadai and Rp 327.000/sqm for the lowest land price was in the village of Tanjung Buntung.…”
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Evaluation of wavelength ranges and tissue depth probed by diffuse reflectance spectroscopy for colorectal cancer detection
Published 2021-01-01“…In this study, we evaluated the diagnostic capabilities of diffuse reflectance spectroscopy (DRS) for CRC detection by building 6 classification models based on support vector machines (SVMs). …”
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Malware detection in memory images using machine learning
Published 2023“…The study also aims to evaluate the generalisation ability of these models when presented with unseen data and investigate their potential for practical application. 6 classification models were trained and evaluated, and the results showed high scores across multiple metrics in cross-validation. …”
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Epileptic Seizure Detection Using Deep Learning Based Long Short-Term Memory Networks and Time-Frequency Analysis: a Comparative Investigation in Machine Learning Paradigm
Published 2022-09-01“…High classification accuracy of 100% (under hold out and 10-fold protocol) and 99.80% (under 10-fold protocol) is achieved by the proposed LSTM strategy followed by the Back Propagation Artificial Neural network (BPANN) which achieves 99.6% classification accuracy when all the 150 EEG biomarkers were used as input to the classifier under 10-fold cross-validation technique. …”
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Accurate and fast identification of minimally prepared bacteria phenotypes using Raman spectroscopy assisted by machine learning
Published 2022-09-01“…We attain more than 96% classification accuracy on a dataset consisting of 15 different classes and 95.6% classification accuracy for six MR–MS bacteria species. …”
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Taxonomy-based data representation for data mining: an example of the magnitude of risk associated with H. pylori infection
Published 2021-08-01“…Results Evaluation of our approach was carried out using 6 classification algorithms that induce rule-based or tree-based classifiers. …”
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Automated algorithms combining structure and function outperform general ophthalmologists in diagnosing glaucoma.
Published 2018-01-01“…The sensitivity at 90% specificity ranged from 51.6% (Classification Tree) to 82.8% (Bagging, Multilayer Perceptron and Support Vector Machine Gaussian). …”
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Applications of Isolated-Check Visual Evoked Potential in Early Stage of Open-Angle Glaucoma Patients
Published 2018-01-01“…Results: Based on an SNR criterion of 1, the icVEP had a sensitivity of 62.2% and a specificity of 92.3% for diagnosing early-stage OAG with 74.6% classification accuracy. The ROC curve analysis, however, suggested that an SNR criterion of 0.93 would produce the highest classification accuracy (77.3%). …”
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Classification of electrically-evoked potentials in the parkinsonian subthalamic nucleus region
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The structure of natural landscapes and its role in the development of the landscape zoning scheme of Belarus
Published 2022-05-01“…The appearance of such information, along with the available data of remote sensing of the Earth and the possibility of application of geoinformation technologies, also allowed the development of new, detailed versions of maps of natural landscapes, both for institutions of higher and general secondary education using 6 classification units. One of them – map for institutions of higher education on a scale of 1: 500 000 – served as the basis for the analysis and identification of patterns of spatial distribution of natural territorial complexes in the rank of subtypes, groups of genera, genera and species of landscapes. …”
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Assessment of mechanical damage to flaxseeds using radiographic imaging and tomography
Published 2022-12-01“…The SVM and LDA classifiers achieved 87.2% and 79.6% classification accuracies, respectively. The developed model confirms that radiographic imaging has the potential to detect mechanical damages of seeds in a rapid, automated, and non-destructive fashion.…”
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Combining DNA methylation and RNA sequencing data of cancer for supervised knowledge extraction
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MALDI-TOF MS as a Novel Tool for the Estimation of Postmortem Interval in Liver Tissue Samples
Published 2017-07-01“…Using genetic algorithm (GA), supervised neural network (SNN), and quick classifier (QC) methods, we built 6 classification models, which showed high recognition capability and good cross-validation. …”
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A Simple Laser-Induced Breakdown Spectroscopy Method for Quantification and Classification of Edible Sea Salts Assisted by Surface-Hydrophilicity-Enhanced Silicon Wafer Substrates
Published 2023-11-01“…Also, the Mg II and Ca II emission peak intensities were used in a <i>k</i>-nearest neighbors model providing 98.6% classification accuracy. In both quantification and classification, intensity normalization using a Na I emission line as a reference signal was effective. …”
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