A New Preprocessing Method for Diabetes and Biomedical Data Classification by Sarbast CHALO, İbrahim Berkan AYDİLEK

“…Several different types of machine learning classifiers, such as KNN, J48, RF, and DT, were utilized in the experimental findings of biological datasets. …”
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Application of Feature Selection Based on Elastic Network and Random Forest in the Evaluation of Sports Effects by Lina Ren, Shen Cao

“…With the rapid development of data mining and machine-learning technology and the outbreak of big sports data mining development challenges, sports data mining cannot simply use data statistical methods such as how to combine machine learning and data mining technology for effective mining and analysis of sports data, to provide useful advice for public physical exercise, and this is an urgent need to study. …”
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Prediction of Sonic Log Values Using a Gradient Boosting Algorithm in the 'AB' Field by Rasif Nahari, Utama Widya, Ardhya Garini Sherly, Fitri Indriani Rista, Pratama Novian Putra Dhea

“…To address missing data, machine learning algorithms, like gradient boosting, provide an effective solution. …”
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An in‐depth study of the effects of methods on the dataset selection of public development projects by Can Cheng, Bing Li, Zengyang Li, Peng Liang, Xu Yang

“…The results show that (1) to select PDPs or DPDPs with a high precision, the base line method is the best with precision of 0.877 (PDPs) and 0.831 (DPDPs); (2) to select PDPs or DPDPs with a high F‐measure, the machine learning methods are the best, with F‐measure of 0.817 (PDPs) and 0.789 (DPDPs); (3) existing sample selection strategies can be combined with the machine learning methods, and the precision of selecting PDPs can be increased by 6.39%–41.33% and the precision of selecting DPDPs can be can be increased by 35.50%–269.02%.…”
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DETECTION OF KERATOCONUS DISEASE DEPENDING ON CORNEAL TOPOGRAPHY USING DEEP LEARNING by Aseel Abdulhasan Hashim, Mahdi Mazinani

“…The pre-processed data is then fed into Machine Learning(ML) algorithms and Convolutional Neural Network(CNN) models, by which the four corneal maps were analyzed. …”
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Artificial Intelligence in Identifying Patients With Undiagnosed Nonalcoholic Steatohepatitis by Onur Baser, Gabriela Samayoa, Nehir Yapar, Erdem Baser

“…We performed a claims data analysis using a machine learning algorithm. To build our model, the study population was randomly divided into an 80% training subset and a 20% testing subset and tested and trained using a cross-validation technique. …”
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INTEGRATING NEURAL NETWORKS INTO SHEET METAL FORMING: A REVIEW OF RECENT ADVANCES AND APPLICATIONS by COSMIN - CONSTANTIN GRIGORAȘ, ȘTEFAN COȘA, VALENTIN ZICHIL

“… In order to predict defects, improve performance, and streamline operations, machine learning techniques are becoming ever more indispensable in manufacturing processes, mainly in sheet metal forming. …”
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Motivation Analysis of Technological Startups Business Models Based on Intelligent Data Mining and Analysis by Xuejiao Ren, Xiaozhou Ding

“…To improve the motivation analysis effect of the technological startups business model, this study combines intelligent data mining technology to analyze related factors and proposes a method of adjusting parameters of machine-learning model based on Bayesian optimization algorithm. …”
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Vers les analyses algorithmiques de l'espace et des territoires by Claire Bailly, Jean Magerand

“…Big data, data mining and machine learning are undergoing unprecedented development. …”
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Evaluation of the Risk of Recurrence in Patients with Local Advanced Rectal Tumours by Different Radiomic Analysis Approaches by Alaa Khadidos, Adil Khadidos, Olfat M. Mirza, Tawfiq Hasanin, Wegayehu Enbeyle, Abdulsattar Abdullah Hamad

“…Using artificial intelligence, in particular, different machine learning techniques, is a necessary step for better data exploitation. …”
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SURVEY AND PROPOSED METHOD TO DETECT ADVERSARIAL EXAMPLES USING AN ADVERSARIAL RETRAINING MODEL by Thanh Son Phan, Quang Hua Ta, Duy Trung Pham, Phi Ho Truong

“…However, in recent years, machine learning models have been the target of various attack methods. …”
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Evaluation of early student performance prediction given concept drift by Benedikt Sonnleitner, Tom Madou, Matthias Deceuninck, Filotas Theodosiou, Yves R. Sagaert

“…We investigate the performance of different machine learning pipelines on a data set with change in study behavior during the Covid-19 period. …”
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Evaluation of Provincial Economic Resilience in China Based on the TOPSIS-XGBoost-SHAP Model by Zhan Wu

“…The aim of this research is to propose a framework for measuring and analysing China’s economic resilience based on the XGBoost machine learning algorithm, using Bayesian optimization (BO) algorithm, extreme gradient-boosting (XGBoost) algorithm, and TOPSIS method to measure China’s economic resilience from 2007 to 2021. …”
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Integrated Bioinformatics Identifies FREM1 as a Diagnostic Gene Signature for Heart Failure by Chenyang Jiang, Weidong Jiang

“…This study is aimed at integrating bioinformatics and machine learning to determine novel diagnostic gene signals in the progression of heart failure disease. …”
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PD_EBM: An Integrated Boosting Approach Based on Selective Features for Unveiling Parkinson's Disease Diagnosis With Global and Local Explanations by Fahmida Khanom, Mohammad Shorif Uddin, Rafid Mostafiz

“…PD_EBM leverages machine learning (ML) algorithms and a hybrid feature selection approach to enhance diagnostic accuracy. …”
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Pulse2AI: An Adaptive Framework to Standardize and Process Pulsatile Wearable Sensor Data for Clinical Applications by Sicong Huang, Roozbeh Jafari, Bobak J. Mortazavi

“…<italic>Goal:</italic> To establish Pulse2AI as a reproducible data preprocessing framework for pulsatile signals that generate high-quality machine-learning-ready datasets from raw wearable recordings. …”
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A Systematic Review Towards Big Data Analytics in Social Media by Md. Saifur Rahman, Hassan Reza

“…This creates the opportunity to make the "Big Social Data" handy by implementing machine learning approaches and social data analytics. …”
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Potato Quality Grading Based on Depth Imaging and Convolutional Neural Network by Qinghua Su, Naoshi Kondo, Dimas Firmanda Al Riza, Harshana Habaragamuwa

“…In this study, we developed a potato automatic grading system that uses a depth imaging system as a data collector and applies a machine learning system for potato quality grading. The depth imaging system collects 3D potato surface thickness distribution data and stores depth images for the training and validation of the machine learning system. …”
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Robust Malware identification via deep temporal convolutional network with symmetric cross entropy learning by Jiankun Sun, Xiong Luo, Weiping Wang, Yang Gao, Wenbing Zhao

“…Nowadays, researchers have made many efforts concerning supervised machine learning methods to identify malicious attacks. …”
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Step-by-step causal analysis of EHRs to ground decision-making. by Matthieu Doutreligne, Tristan Struja, Judith Abecassis, Claire Morgand, Leo Anthony Celi, Gaël Varoquaux

“…Causal inference enables machine learning methods to estimate treatment effects of medical interventions from electronic health records (EHRs). …”
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