Investigating of Machine Learning Based Algorithms for Liver Cirrhosis Prediction by Young Choi, Eunsung Oh

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Creation and interpretation of machine learning models for aqueous solubility prediction by Minyi Su, Enric Herrero

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

“… Extending technologies and data development culminated in the need for quicker and more reliable processing of massive data sets. Machine Learning techniques are used excessively. This paper, therefore, attempts to deal with data processing, using a support vector machine (SVM) algorithm in different fields since it is a reliable, efficient classification method in the area of machine learning. …”
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Design of System-of-System Acquisition Analysis Using Machine Learning by Fahad H. Alshammari

“…In the last few decades, machine learning and data analytics have been widely used in system design and acquisitions. …”
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Prediction of Rooftop Photovoltaic Solar Potential Using Machine Learning by K. Mukilan, K. Thaiyalnayaki, Yagya Dutta Dwivedi, J. Samson Isaac, Amarjeet Poonia, Arvind Sharma, Essam A. Al-Ammar, Saikh Mohammad Wabaidur, B. B. Subramanian, Adane Kassa

“…In this paper, we develop a prediction of solar potential across large photovoltaic panels from the roof tops using a machine learning method. The Restricted Boltzmann Machine (RBM) is the machine learning method used in the study to predict or forecast the solar potential in rooftops. …”
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The Use of Machine Learning Methods in Road Safety Research in Poland by Anna Borucka, Sebastian Sobczuk

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On Internet Traffic Classification: A Two-Phased Machine Learning Approach by Taimur Bakhshi, Bogdan Ghita

“…This paper aims to overcome these challenges by proposing two-phased machine learning classification mechanism with NetFlow as input. …”
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The impact of dietary fiber on colorectal cancer patients based on machine learning by Xinwei Ji, Lixin Wang, Pengbo Luan, Jingru Liang, Weicai Cheng

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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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Anomaly Detection in Network Traffic Using Advanced Machine Learning Techniques by Stephanie Ness, Vishwanath Eswarakrishnan, Harish Sridharan, Varun Shinde, Naga Venkata Prasad Janapareddy, Vineet Dhanawat

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New Trend: Application of Laser-Induced Breakdown Spectroscopy with Machine Learning by Zhe Wang

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Research on Personal Loan Default Risk Assessment Based on Machine Learning by Liu Guangsen

“…Among them, the Deep Neural Network has the best overall performance compared to the other three machine learning models. The research in this paper has certain research significance for the research of machine learning in personal loan default risk assessment.…”
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Prediction of growth and feed efficiency in mink using machine learning algorithms by A. Shirzadifar, G. Manafiazar, P. Davoudi, D. Do, G. Hu, Y. Miar

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Accelerated enzyme engineering by machine-learning guided cell-free expression by Grant M. Landwehr, Jonathan W. Bogart, Carol Magalhaes, Eric G. Hammarlund, Ashty S. Karim, Michael C. Jewett

“…To address this challenge, we develop a machine learning (ML)-guided platform that integrates cell-free DNA assembly, cell-free gene expression, and functional assays to rapidly map fitness landscapes across protein sequence space and optimize enzymes for multiple, distinct chemical reactions. …”
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Digital Management and Optimization of Tourism Information Resources Based on Machine Learning by Xueqiu Zhuang, Huihua Jiao, Li Kang

“…The digital management of tourism information resources based on machine learning can optimize the tourism industry and promote its development.…”
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Rapid literature mapping on the recent use of machine learning for wildlife imagery by Nakagawa, Shinichi, Lagisz, Malgorzata, Francis, Roxane, Tam, Jessica, Li, Xun, Elphinstone, Andrew, Jordan, Neil R., O'Brien, Justine K., Pitcher, Benjamin J., Van Sluys, Monique, Sowmya, Arcot, Kingsford, Richard T.

“…., camera traps, or drones), 3) study locations, 4) alternative machine learning algorithms, 5) outcomes (e.g., recognition, classification, or tracking), 6) reporting quality and openness, 7) author affiliation, and 8) publication journal types. …”
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Machine learning-assisted development of gas separation membranes: A review by An Li, Jianchun Chu, Shaoxuan Huang, Yongqi Liu, Maogang He, Xiangyang Liu

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Machine Learning for Ischemic Heart Disease Diagnosis Aided by Evolutionary Computing by Mohammad Alsaffar, Abdullah Alshammari, Gharbi Alshammari, Saud Aljaloud, Tariq S. Almurayziq, Fadam Muteb Abdoon, Solomon Abebaw

“…In light of these findings, a hybrid diagnostic tool has been developed that combines several computational intelligence (machine learning) techniques capable of analyzing clinical histories and images of electrocardiogram signals and indicating whether or not the patient has ischemic heart disease with up to 97.01% accuracy. …”
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Multiple Machine Learning Algorithms-based NBA Team Playoffs Prediction by Yeung Manho

“…With the rapid development of data analytics in sports, it is vital to use machine learning methods to make decisions and predictions. …”
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Comparative analysis of machine learning approaches for predicting the risk of vaginal laxity by Hongguo Zhao, Peng Liu, Fei Chen, Mengjuan Wang, Jiaxi Liu, Xiling Fu, Hang Yu, Manman Nai, Lei Li, Xinbin Li

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