WoFSCast: A Machine Learning Model for Predicting Thunderstorms at Watch‐to‐Warning Scales by Montgomery L. Flora, Corey Potvin

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Forecasting the Sugarcane Yields Based on Meteorological Data Through Ensemble Learning by Sumit Kumar, Millie Pant, Atulya Nagar

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A systematic mapping to investigate the application of machine learning techniques in requirement engineering activities by Shoaib Hassan, Qianmu Li, Khursheed Aurangzeb, Affan Yasin, Javed Ali Khan, Muhammad Shahid Anwar

“…Abstract Over the past few years, the application and usage of Machine Learning (ML) techniques have increased exponentially due to continuously increasing the size of data and computing capacity. …”
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Stacked Ensemble Learning for Classification of Parkinson’s Disease Using Telemonitoring Vocal Features by Bolaji A. Omodunbi, David B. Olawade, Omosigho F. Awe, Afeez A. Soladoye, Nicholas Aderinto, Saak V. Ovsepian, Stergios Boussios

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Relaxing the confirmatory factor model in the Big Five: Exploratory, Bayesian, and machine learning approaches by Jacob S. Gray

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Intelligent Data Processing Methods for Studying the Influence of the Environment on the Morbidity of the Population in Moscow by T. V. Zolotova, A. S. Marunko

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An Analysis of the Severity of Alcohol Use Disorder Based on Electroencephalography Using Unsupervised Machine Learning by Kaloso M. Tlotleng, Rodrigo S. Jamisola

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Machine learning and deep learning in medicine and neuroimaging by Iván Sánchez Fernández, Jurriaan M. Peters

“…Machine learning is starting to be successfully applied to several areas of medicine, including predictive analytics, decision support, natural language processing of free‐text notes, and automatic interpretation of electrophysiological recordings. …”
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A Comprehensive Analysis of Fake News Detection Models: A Systematic Literature Review and Current Challenges by Alok Mishra, Halima Sadia

“…Our study focuses on how machine learning and deep learning algorithms are used to detect fraudulent data. …”
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A Hybrid Regression–Kriging–Machine Learning Framework for Imputing Missing TROPOMI NO₂ Data over Taiwan by Alyssa Valerio, Yi-Chun Chen, Chian-Yi Liu, Yi-Ying Chen, Chuan-Yao Lin

“…This study presents a novel application of a hybrid regression–kriging (RK) and machine learning (ML) framework to impute missing tropospheric NO₂ data from the TROPOMI satellite over Taiwan during the winter months of January, February, and December 2022. …”
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Federated Learning-Based Credit Card Fraud Detection: A Comparative Analysis of Advanced Machine Learning Models by Zheng Han

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Analysis and Optimization of Customer Lifetime Value Prediction using Machine Learning and Deep Learning Models by RFM Techniques by Leila Taherkhani, Amir Daneshvar, Hossein Amoozad Khalili, MohammadReza Sanaei

“…This study analyse the prediction of Customer Lifetime Value (CLV) using machine learning models—Linear Regression, Random Forest, and LightGBM—trained on features derived from hotel website interactions and booking records. …”
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DDoS Attack Detection in IoT: A Comparative Resource and Performance Analysis of Deep Learning and Machine Learning Models by Amer Abualhassan, Irfan Rashid, Farid Binbeshr, Muhammad Imam

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Machine Learning System for Predicting Cardiovascular Disorders in Diabetic Patients by A. Mayya, H. Solieman

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Comparative Analysis of Machine Learning and Deep Learning Models for Lung Cancer Prediction Based on Symptomatic and Lifestyle Features by Bireswar Dutta

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AI-Based Breast Cancer Detection System: Deep Learning and Machine Learning Approaches for Ultrasound Image Analysis by Amro Moursi, Abdulrahman Aboumadi, Uvais Qidwai

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Prediction of Hypertension in the Pediatric Population Using Machine Learning and Transfer Learning: A Multicentric Analysis of the SAYCARE Study by Keisyanne Araujo-Moura, Letícia Souza, Tiago Almeida de Oliveira, Mateus Silva Rocha, Augusto César Ferreira De Moraes, Alexandre Chiavegatto Filho

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Category-Based Sentiment Analysis of Sindhi News Headlines Using Machine Learning, Deep Learning, and Transformer Models by Safdar Ali Soomro, Siti Sophiayati Yuhaniz, Mazhar Ali Dootio, Ghulam Mujtaba, Jawaid Ahmed Siddiqui

“…To evaluate the effectiveness of different machine learning (ML), deep learning (DL), and transformer-based approaches, we conduct a comparative analysis of various models on SA and category classification tasks. …”
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ANALYSIS OF THE APPLICATIONS OF THE DATA-DRIVEN APPROACH IN EVALUATING THE THERMAL-PHYSICAL PROPERTIES OF COMPOSITES by Ruslan Lavshchenko, Gennadiy Lvov

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Optimizing quantum convolutional neural network architectures for arbitrary data dimension by Changwon Lee, Israel F. Araujo, Dongha Kim, Junghan Lee, Siheon Park, Ju-Young Ryu, Ju-Young Ryu, Daniel K. Park, Daniel K. Park

“…Quantum convolutional neural networks (QCNNs) represent a promising approach in quantum machine learning, paving new directions for both quantum and classical data analysis. …”
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