Teaching Quality Evaluation of Ideological and Political Courses in Colleges and Universities Based on Machine Learning by Lijun Qiao

“…This paper combines teaching evaluation theory and machine learning methods, analyzes the rationality of evaluation indicators through the acquired evaluation data, and optimizes the evaluation system. …”
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Predicting the Link between Stock Prices and Indices with Machine Learning in R Programming Language by Mengya Cao

“…This paper provides an in-depth analysis machine study of the relationship between stock prices and indices through machine learning algorithms. Stock prices are difficult to predict by a single financial formula because there are too many factors that can affect stock prices. …”
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Data-driven evaluation of background radiation safety using machine learning and statistical analysis by Muhammad Abid, Muhammad Shahid

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Identification of depressive symptoms in adolescents using machine learning combining childhood and adolescence features by Xinzhu Liu, Rui Cang, Zihe Zhang, Ping Li, Hui Wu, Wei Liu, Shu Li

“…These symptoms may be linked to various factors experienced during both childhood and adolescence. Machine learning (ML) has attracted substantial attention in the field of adolescent depression; however, studies establishing prediction models have primarily considered childhood or adolescent features separately, resulting in a lack of analyses that incorporate factors from both stages. …”
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Smell-ML: A Machine Learning Framework for Detecting Rarely Studied Code Smells by Esraa Hamouda, Abeer El-Korany, Soha Makady

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An Intelligent Carbon-Based Prediction of Wastewater Treatment Plants Using Machine Learning Algorithms by Anwer Mustafa Hilal, Maha M. Althobaiti, Taiseer Abdalla Elfadil Eisa, Rana Alabdan, Manar Ahmed Hamza, Abdelwahed Motwakel, Mesfer Al Duhayyim, Noha Negm

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The Application of Supervised Machine Learning Algorithms for Image Alignment in Multi-Channel Imaging Systems by Kyrylo Romanenko, Yevgen Oberemok, Ivan Syniavskyi, Natalia Bezugla, Pawel Komada, Mykhailo Bezuglyi

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Evaporation Rate Prediction Using Advanced Machine Learning Models: A Comparative Study by Zainab Abdulelah Al Sudani, Golam Saleh Ahmed Salem

“…In this study, four machine learning (ML) modeling approaches, extreme learning machine (ELM), gradient boosting machine (GBM), quantile random forest (QRF), and Gaussian process regression (GPR), have been developed to estimate the monthly evaporation loss over two stations located in Iraq. …”
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Forecasting Stock Prices of Companies Producing Solar Panels Using Machine Learning Methods by Zaffar A. Shaikh, Andrey Kraikin, Alexey Mikhaylov, Gabor Pinter

“…The recurrent neural network LSTM is used in the article and this approach is based on complexity theory. Machine learning technologies are now being actively implemented in various sectors of the economy and are considered effective. …”
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Retracted: Modeling Social Network of Professional Sports Athletes Based on Machine Learning Algorithms by International Transactions on Electrical Energy Systems

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Correction: Enhanced wave overtopping simulation at vertical breakwaters using machine learning algorithms. by PLOS One Staff

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Analyzing Rail Traffic Diversion Based on Machine Learning Technique considering Transportation Security by Jing Luo, Dai Zhou, Wenjun Ma, Guohua Zhao

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Decoding cortical folding patterns in marmosets using machine learning and large language model by Yue Wu, Xuesong Gao, Zhengliang Liu, Pengcheng Wang, Zihao Wu, Yiwei Li, Tuo Zhang, Tianming Liu, Tao Liu, Xiao Li

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Detection of mite infested saffron plants using aerial imaging and machine learning classifier by Hossein Sahabi, Jalal Baradaran-Motie

“… Aim of study: To evaluate and develop a machine learning code that uses aerial images in visible and near infrared (NIR) spectra to detect mite-infested Saffron (Crocus sativus L.) plants through processing the spectral indices to classify healthy and diseased plants. …”
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Enhancing Medical Diagnostics with Machine Learning: A Study on Ensemble Methods and Transfer Learning by Zhang Jiaming

“…This paper explores the use of machine learning (ML) in medicine, emphasizing how important it is to enhance patient outcomes and diagnostic precision. …”
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A Machine Learning Model for Predicting Prognosis in HCC Patients With Diabetes After TACE by Wu L, Chen L, Zhang L, Liu Y, Ouyang D, Wu W, Lei Y, Han P, Zhao H, Zheng C

“…Therefore, this study aimed to establish and validate a machine learning-based explainable prediction model of prognosis in patients with HCC and T2DM undergoing transarterial chemoembolization (TACE).Patients and Methods: The prediction model was developed using data from the derivation cohort comprising patients from three medical centers, followed by external validation utilizing patient data extracted from another center. …”
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Research on Traffic Accident Severity Level Prediction Model Based on Improved Machine Learning by Jiming Tang, Yao Huang, Dingli Liu, Liuyuan Xiong, Rongwei Bu

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Reply to: comment on “Early cancer detection by serum biomolecular fingerprinting spectroscopy with machine learning” by Shilian Dong, Dong He, Qian Zhang, Chaoning Huang, Zhiheng Hu, Chenyang Zhang, Lei Nie, Kun Wang, Wei Luo, Jing Yu, Bin Tian, Wei Wu, Xu Chen, Fubing Wang, Jing Hu, Xiangheng Xiao

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Machine Learning-Based Quantification of Lateral Flow Assay Using Smartphone-Captured Images by Anne M. Davis, Asahi Tomitaka

Subjects: “…machine learning…”
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Adulteration detection in cactus seed oil: Integrating analytical chemistry and machine learning approaches by Said El Harkaoui, Cristina Ortiz Cruz, Aaron Roggenland, Micha Schneider, Sascha Rohn, Stephan Drusch, Bertrand Matthäus

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