A Quantum-Based Machine Learning Approach for Autism Detection Using Common Spatial Patterns of EEG Signals by S. Saranya, R. Menaka

“…Electroencephalography (EEG) has emerged as a non-invasive tool to capture brain activity and facilitate the early detection of ASD using machine learning techniques. However, attaining high accuracy with minimal EEG channels remains a challenge. …”
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Dynamics of Cropland Non-Agriculturalization in Shaanxi Province of China and Its Attribution Using a Machine Learning Approach by Huiting Yan, Hao Chen, Fei Wang, Linjing Qiu

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An extensive bibliometric analysis of pavement deterioration detection using sensors and machine learning: Trends, innovations, and future directions by Mehmet Rizelioğlu

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Fault diagnosis of a CNC hobbing cutter through machine learning using three axis vibration data by Nagesh Tambake, Bhagyesh Deshmukh, Sujit Pardeshi, Sachin Salunkhe, Robert Cep, Emad Abouel Nasr

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Following intravenous thrombolysis, the outcome of diabetes mellitus associated with acute ischemic stroke was predicted via machine learning by Xiaoqing Liu, Miaoran Wang, Rui Wen, Haoyue Zhu, Ying Xiao, Qian He, Yangdi Shi, Zhe Hong, Bing Xu

“…An 80/20 train-test split was implemented for model development and validation, employing various machine learning classifiers, including artificial neural networks (ANN), random forest (RF), XGBoost (XGB), and LASSO regression. …”
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Machine learning techniques for IoT security: Current research and future vision with generative AI and large language models by Fatima Alwahedi, Alyazia Aldhaheri, Mohamed Amine Ferrag, Ammar Battah, Norbert Tihanyi

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Comparative analysis of the human microbiome from four different regions of China and machine learning-based geographical inference by Yinlei Lei, Min Li, Han Zhang, Yu Deng, Xinyu Dong, Pengyu Chen, Ye Li, Suhua Zhang, Chengtao Li, Shouyu Wang, Ruiyang Tao

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Application of the Machine Learning Methods to Assess the Impact of physico-chemical characteristics of water on Feed Consumption in Fish Farms by Hava Şimşek, Mükerrem Oral, Mesut Yılmaz, Mustafa Çakır, Nedim Özdemir, Okan Oral

“…Machine learning (ML) methods, which are one of the subfields of artificial intelligence (AI) and have gained popularity in applications in recent years, play an important role in solving many challenges in aquaculture. …”
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Species identification for Indian seafood markets: A machine learning approach with a fish datasetMendeley Data by Priyanka Paygude, Namita Shinde, Amol Dhumane, Geeta S. Navale, Prashant Chavan, Atul Kathole, Vijaykumar Bidve

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Development and application of machine learning models in US consumer price index forecasting: Analysis of a hybrid approach by Yunus Emre Gur

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Dynamic Behavior Analysis of Touchdown Process in Active Magnetic Bearing System Based on a Machine Learning Method by Zhe Sun, Xunshi Yan, Jingjing Zhao, Xiao Kang, Guojun Yang, Zhengang Shi

“…In this model, some specific mechanical parameters are regarded as functions of deformation of auxiliary bearing and velocity of rotor firstly; furthermore, a machine learning method is utilized to model these function relationships. …”
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Retracted: Implementing Machine Learning for Supply-Demand Shifts and Price Impacts in Farmer Market for Tool and Equipment Sharing by Journal of Food Quality

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Machine learning approaches for predicting and validating mechanical properties of Mg rare earth alloys for light weight applications by Sandeep Jain, Ayan Bhowmik, Jaichan Lee

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Understanding the spread of agriculture in the Western Mediterranean (6th-3rd millennia BC) with Machine Learning tools by Maria Elena Castiello, Emmanuele Russo, Héctor Martínez-Grau, Ana Jesus, Georgina Prats, Ferran Antolín

“…Here, we tackle this question by compiling data and proxies at a superregional and multi-scale level, including archaeobotanical information, radiocarbon dates and paleoclimatic models, then applying a machine learning approach to investigate the impact of ecological and climatic constraints on the first Neolithic humans and crops. …”
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Multi-Person Localization Based on a Thermopile Array Sensor with Machine Learning and a Generative Data Model by Stefan Klir, Julian Lerch, Simon Benkner, Tran Quoc Khanh

“…Current research has shown that there are two machine learning-based algorithms that are particularly prominent for general object detection: You Only Look Once (YOLOv5) and Detection Transformer (DETR). …”
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Machine Learning-Based Anomaly Prediction for Proactive Monitoring in Data Centers: A Case Study on INFN-CNAF by Andrea Asperti, Gabriele Raciti, Elisabetta Ronchieri, Daniele Cesini

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Feature Selection in Cancer Classification: Utilizing Explainable Artificial Intelligence to Uncover Influential Genes in Machine Learning Models by Matheus Dalmolin, Karolayne S. Azevedo, Luísa C. de Souza, Caroline B. de Farias, Martina Lichtenfels, Marcelo A. C. Fernandes

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A comprehensive overview of acupuncture therapy over the past 20 years: Machine learning-based bibliometric analysis by Chen Liu, Shuqing Liu, Yu Wang, Xinyi Xia, Yu Zhang, Huili Jiang, Tuya Bao, Xuehong Ma

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Identifying natural inhibitors against FUS protein in dementia through machine learning, molecular docking, and dynamics simulation by Darwin Li

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Machine learning-based prediction of in-hospital mortality for critically ill patients with sepsis-associated acute kidney injury by Tianyun Gao, Zhiqiang Nong, Yuzhen Luo, Manqiu Mo, Zhaoyan Chen, Zhenhua Yang, Ling Pan

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