Machine Learning ECG Classification Using Wavelet Scattering of Feature Extraction by Heyam A. Marzog, Haider. J. Abd

“…The highest accuracy of classification performance for machine learning approaches are 99.7 for neural network with wavelet scattering features extraction and 99.92 for SVM also with wavelet scattering features extraction. …”
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TLE1 Positive Clear Cell Sarcoma of the Kidney: A Case Report and Review of the Literature by Rana Naous

“…Although there have been previous case reports of CCSK with positive expression of CD99 and negative TLE1, to our knowledge, this is the first case of CCSK expressing both CD99 and TLE1.…”
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Mathematical modelling and control of echinococcus in Qinghai province, China by Liumei Wu, Baojun Song, Wen Du, Jie Lou

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Dust Explosion Characteristics of Agglomerated 35 nm and 100 nm Aluminum Particles by Hong-Chun Wu, Hsin-Jung Ou, Deng-Jr Peng, Hsiao-Chi Hsiao, Chung-Yun Gau, Tung-Sheng Shih

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Levo-Tetrahydropalmatine Attenuates Bone Cancer Pain by Inhibiting Microglial Cells Activation by Mao-yin Zhang, Yue-peng Liu, Lian-yi Zhang, Dong-mei Yue, Dun-yi Qi, Gong-jian Liu, Su Liu

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Global, regional, and national survey on burden and Quality of Care Index (QCI) of orofacial clefts: Global burden of disease systematic analysis 1990-2019. by Ahmad Sofi-Mahmudi, Erfan Shamsoddin, Sahar Khademioore, Yeganeh Khazaei, Amin Vahdati, Marcos Roberto Tovani-Palone

“…In the year 2019, the top five countries with the highest QCI scores were as follows: Norway (QCI = 99.9), Ireland (99.4), France (99.4), Germany (99.3), the Netherlands (99.3), and Malta (99.3). …”
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Clasificación de cáncer de mama con técnicas de análisis de la componente principal-Kernel PCA, algoritmos de máquina de vectores de soporte y regresión logística by Rosana Pirchio

“…Los mejores resultados de las métricas fueron para PCA 2 y 4(0,99; 0,99; 1; 0,99; 0,99). Para el training set con datos originales fueron 0,96; 0,95; 0,99; 0,97; 0,95. …”
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Béatrice Galinon-Mélénec (dir.), L’Homme trace : perspectives anthropologiques des traces contemporaines by Annick Monseigne

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UMTS中切换的系统开销 by 张铎, 卫国, 朱近康

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An Ensemble Learning Based Intrusion Detection Model for Industrial IoT Security by Mouaad Mohy-Eddine, Azidine Guezzaz, Said Benkirane, Mourade Azrour, Yousef Farhaoui

“…RF-PCCIF and RF-IFPCC show noteworthy results with 99.98% and 99.99% Accuracy (ACC) and 6.18 s and 6.25 s prediction time on Bot-IoT, respectively. …”
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Comparative Analysis of the Effect Dual Spark Ignition and Single Spark Ignition on Performance and Exhaust Emissions in Bioethanol-Fueled Engines by Avita Ayu Permanasari, Ahmad Faizal Wahidin, Hasan Ismail, Erwin Komara, Poppy Puspitasari, Gina A. Lorenzo

“…NOx emission increased when using 99% bioethanol on the DSI engine by 15.58% compared to the SSI engine. …”
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Malaria Disease Prediction Based on Convolutional Neural Networks by Dhrgam AL Kafaf, Noor N. Thamir, Samara S. AL-Hadithy

“…Exhibiting a precision rate of 99.59%, a specificity measure of 99.69%, an Sensitivity of 99.40%, F1 Measurement of 99.44%, and a Precision of 99.48, it showcases its capacity to effectively distinguish betwixt malaria-afflicted cells and unafflicted cells. …”
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Deep learning-based malaria parasite detection: convolutional neural networks model for accurate species identification of Plasmodium falciparum and Plasmodium vivax by Diego A. Ramos-Briceño, Alessandro Flammia-D’Aleo, Gerardo Fernández-López, Fhabián S. Carrión-Nessi, David A. Forero-Peña

“…The model’s accuracy reached 99.51%, a precision of 99.26%, a recall of 99.26%, a specificity of 99.63%, an F1 score of 99.26%, and a loss of 2.3%. …”
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Analytical Approximate Solutions for the Cubic-Quintic Duffing Oscillator in Terms of Elementary Functions by A. Beléndez, M. L. Alvarez, J. Francés, S. Bleda, T. Beléndez, A. Nájera, E. Arribas

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Imaging the Met Receptor Tyrosine Kinase (Met) and Assessing Tumor Responses to a Met Tyrosine Kinase Inhibitor in Human Xenograft Mouse Models with a [Tc] (AH-113018) or CY 5** (A... by Elaine M. Jagoda, Sibaprasad Bhattacharyya, Joseph Kalen, Lisa Riffle, Avrum Leeder, Stephanie Histed, Mark Williams, Karen J. Wong, Biying Xu, Lawrence P. Szajek, Osama Elbuluk, Fabiola Cecchi, Kristen Raffensperger, Meghana Golla, Donald P. Bottaro, Peter Choyke

“…A peptide targeting Met labeled with [ 99m Tc] had high affinity in vitro (K d = 3.3 nM) and detected relative changes in Met in human cancer cell lines. …”
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An automatic cervical cell classification model based on improved DenseNet121 by Yue Zhang, Chunyu Ning, Wenjing Yang

“…The accuracy of A2SDNet121 for two and seven-classification tasks on the Herlev dataset is 99.75% and 99.14%, respectively. The accuracy for two, three, and five-classification tasks on the SIPaKMeD dataset reaches 99.55%, 99.75% and 99.22%, respectively. …”
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Use of a Ray-Based Reconstruction Algorithm to Accurately Quantify Preclinical MicroSPECT Images by Bert Vandeghinste, Roel Van Holen, Christian Vanhove, Filip De Vos, Stefaan Vandenberghe, Steven Staelens

“…For 99m Tc, an uncorrected quantification error of 28 ± 3% is reduced to 8 ± 3%. …”
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La contratación pública como sistema by Carolina Madrid

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Approach to Stability Analysis for Surrounding Rock of Underground Powerhouse by LIU Yuan-xun, DENG Shu-hao

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Wittgenstein, Ludwig. Escrito a máquina. Traducción, introducción y notas críticas de Jesús Padilla Gálvez. Madrid: Trotta, 2014. 694 pp. by Margareth Mejía Génez

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