Author Correction: Classification of distinct tendinopathy subtypes for precision therapeutics by Chenqi Tang, Zetao Wang, Yuanhao Xie, Yang Fei, Junchao Luo, Canlong Wang, Yue Ying, Peiwen He, Ruojing Yan, Yangwu Chen, Jiayun Huang, Yiwen Xu, Zicheng Wang, Boon Chin Heng, Hengzhi Liu, Jianyou Li, Zi Yin, Haobo Wu, Weishan Chen, Hongwei Ouyang, Xiao Chen, Weiliang Shen

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A new classification for dislocated and displaced proximal humeral fractures by Sadaki Mitsuzawa, Hisataka Takeuchi, Kenta Ijiri, Yuya Furusho, Shinnosuke Yamashita, Yoshihiro Tsukamoto, Satoshi Ota, Eijiro Onishi, Tadashi Yasuda

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Classification of Agricultural Emissions Among OECD Countries with Unsupervised Techniques by Adam Andrzejuk

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Malware classification method based on static multiple-feature fusion by Bo-wen SUN, Yan-yi HUANG, Qiao-kun WEN, Bin TIAN, Peng WU, Qi LI

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Contestations Over Classifications: Latinos, the Census and Race in the United States by Clara E. Rodríguez

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Machine Learning Applications based on SVM Classification A Review by Dakhaz Mustafa Abdullah, Adnan Mohsin Abdulazeez

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Preliminary Study of Bioinformatics Patents and Their Classifications Registered in the KIPRIS Database by Hyun-Seok Park

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Cancer Classification Using Pattern Recognition and Computer Vision Techniques by Haddou Bouazza Sara, Haddou Bouazza Jihad

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Hybrid clustering strategies for effective oversampling and undersampling in multiclass classification by Amirreza Salehi, Majid Khedmati

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Optimization of VGG-16 Accuracy for Fingerprint Pattern Imager Classification by Agus Andreansyah, Julian Supardi

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Sociology of Russophilia in Azerbaijan: A Classification for Russophile Social Groups by Jahandar Jabarov

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Advanced Cancer Classification Using AI and Pattern Recognition Techniques by Haddou Bouazza Sara, Haddou Bouazza Jihad

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Proposed Classification of Midline Lingual Canal: A CBCT Study by Mansi A. Khatri, Yesha V. Jani, Reeta Jha, Deepankar Misra, Siddharth G. Modi, Harmi Patel

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Dilated SE-DenseNet for brain tumor MRI classification by Yuannong Mao, Jiwook Kim, Lena Podina, Mohammad Kohandel

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Deep Learning Approach for Ascaris lumbricoides Parasite Egg Classification by Narut Butploy, Wanida Kanarkard, Pewpan Maleewong Intapan

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Machine Learning Models for Artist Classification of Cultural Heritage Sketches by Gianina Chirosca, Roxana Rădvan, Silviu Mușat, Matei Pop, Alecsandru Chirosca

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Flood Period Classification Forecast Based on Information Fusion and Recognition by XIE Zhigao, LIU Xia, WU Hengqing, LIU Jin

“…To solve the low simulation accuracy of flood forecast models caused by limited historical flood data in river basins,this paper employs the K-means clustering method to cluster typical floods by taking reservoir A as the research object.Meanwhile,it analyzes hydrological influencing factors such as rainfall intensity,rainfall center,and weather system,calculates various parameters of confluence models through a genetic optimization algorithm,and adopts a rough set method to explore the relationship between influencing factors and flood period confluence patterns.Finally,the flood period classification forecast based on information fusion and recognition is conducted.The results are as follows:① The absolute and relative errors of the four selected typical floods calculated by the classification forecast method are 9.01 m³/s and 2.95%,116.46 m³/s and 6.78%,30.92 m³/s and 17.55%,and 6.12 m³/s and 1.86% respectively;② The simulation accuracy of the flood classification forecast model built in this paper is higher than that of the traditional forecast methods,and the determination coefficients of different typical floods are all above 0.8.The results can provide references for the flood period classification and forecast in north China and other regions with less flood data.…”
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Classification of Melanoma Cancer Using Deep Convolutional Neural Networks by Emrah Dönmez, Ali Güneş

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Multi-Label Classification Algorithm for Adaptive Heterogeneous Classifier Group by Meng Han, Shurong Yang, Hongxin Wu, Jian Ding

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Peculiarities of natural honey classification in the course of forensic commodity examination by P. P. Kanivets

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