Prediction of Percutaneous Coronary Intervention Success in Patients With Moderate to Severe Coronary Artery Calcification Using Machine Learning Based on Coronary Angiography: Pro... by Zixiang Ye, Zhangyu Lin, Enmin Xie, Chenxi Song, Rui Zhang, Hao-Yu Wang, Shanshan Shi, Lei Feng, Kefei Dou

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AI in Medical Questionnaires: Innovations, Diagnosis, and Implications by Xuexing Luo, Yiyuan Li, Jing Xu, Zhong Zheng, Fangtian Ying, Guanghui Huang

“…Despite the positive findings, only 21% (3/14) of the studies had entered the clinical validation phase, whereas the remaining 79% (11/14) were still in the exploratory phase of research. …”
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The coverage method of unmanned aerial vehicle mounted base station sensor network based on relative distance by Taifei Zhao, Hua Wang, Qianwen Ma

“…The simulation results show that the coverage of the proposed algorithm is 22.4% higher than that of random deployment, and it is 9.9%, 4.7% and 2.1% higher than similar virtual force-oriented node, circular binary segmentation and hybrid local virtual force algorithms.…”
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Predicting Livestock Farmers’ Attitudes towards Improved Sheep Breeds in Ahar City through Data Mining Methods by Jabraeil Vahedi, Masoumeh Niazifar, Mohammad Ghahremanzadeh, Akbar Taghizadeh, Soheila Abachi, Valiollah Palangi, Maximilian Lackner

“…Next, we employed data mining-based methods, including multilayer perceptron neural networks, random forest, and random tree algorithms. These helped identify essential variables affecting ranchers’ attitudes. …”
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Characteristics and Rapid Prediction of Seismic Subsidence of Saturated Seabed Foundation with Interbedded Soft Clay–Sand by Liuyuan Zhao, Miaojun Sun, Jianhong Ye, Fuqin Yang, Kunpeng He

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Enhancing Software Defect Prediction Using Ensemble Techniques and Diverse Machine Learning Paradigms by Ayesha Siddika, Momotaz Begum, Fahmid Al Farid, Jia Uddin, Hezerul Abdul Karim

“…The prediction of software defects is a crucial element in maintaining the stability and reliability of software systems. This research addresses this need by combining advanced techniques (ensemble techniques) with seventeen machine learning algorithms for predicting software defects, categorised into three types: semi-supervised, self-supervised, and supervised. …”
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Improving Attack Detection in IoV with Class Balancing and Feature Selection by Thierry Widyatama, Ifan Rizqa, Fauzi Adi Rafrastara

“…The ensemble algorithms evaluated in this research comprise Random Forest, Gradient Boosting, and XGBoost. …”
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Optimizing ensemble learning for satellite-based multi-hazard monitoring and susceptibility assessment of landslides, land subsidence, floods, and wildfires by Seyed Vahid Razavi-Termeh, Abolghasem Sadeghi-Niaraki, Farman Ali, Biswajeet Pradhan, Soo-Mi Choi

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Elicitation of Norwegian EQ-5D-5L values for hypothetical and experience-based health states based on the EuroQol Valuation Technology (EQ-VT) protocol by Knut Stavem, Tonya Moen Hansen, Ylva Helland, Liv Ariane Augestad, Kim Rand, Andrew Garratt

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Wavelet-Based ensembled intelligent technique for a better quality of fault detection and classification in AC microgrids by Nityananda Giri, Pravati Nayak, Ranjan Kumar Mallick, Sairam Mishra, Aymen Flah, Habib Kraiem, Lukas Prokop, Mohammad Kanan

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Prediction of copper contamination in soil across EU using spectroscopy and machine learning: Handling class imbalance problem by Chongchong Qi, Nana Zhou, Tao Hu, Mengting Wu, Qiusong Chen, Han Wang, Kejing Zhang, Zhang Lin

“…To address this limitation, we conducted a comprehensive evaluation of three basic machine learning (ML) algorithms and four imbalanced ML algorithms. …”
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Combined L-Band Polarimetric SAR and GPR Data to Develop Models for Leak Detection in the Water Pipeline Networks by Yuyao Zhang, Hongliang Guan, Fuzhou Duan

“…The model features are selected with the Boruta wrapper algorithm based on the SAOCOM-1A images after pre-processing, and the SSRDC values at sampling locations within the research area are calculated with the reflected wave method based on the GPR data. …”
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Residential Building Renovation Considering Energy, Carbon Emissions, and Cost: An Approach Integrating Machine Learning and Evolutionary Generation by Rudai Shan, Wanyu Lai, Huan Tang, Xiangyu Leng, Wei Gu

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Scientific and Engineering Proposals for Improving the Noise Immunity of Receiving Multi-Position Signals in Channels with Variable Parameters by M. R. Bibarsov, S. V. Dvornikov, A. F. Kryachko, A. V. Pshenichnikov

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Learning Optimal Dynamic Treatment Regime from Observational Clinical Data through Reinforcement Learning by Seyum Abebe, Irene Poli, Roger D. Jones, Debora Slanzi

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Enhancing Tire Condition Monitoring through Weightless Neural Networks Using MEMS-Based Vibration Signals by Siddhant Arora, Sridharan Naveen Venkatesh, Vaithiyanathan Sugumaran, Anoop Prabhakaranpillai Sreelatha, Vetri Selvi Mahamuni

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Classifying the Mortality of People with Underlying Health Conditions Affected by COVID-19 Using Machine Learning Techniques by Rami Mustafa A. Mohammad, Malak Aljabri, Menna Aboulnour, Samiha Mirza, Ahmad Alshobaiki

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Development and Validation of DIANA (Diabetes Novel Subgroup Assessment tool): A web-based precision medicine tool to determine type 2 diabetes endotype membership and predict indi... by Viswanathan Baskar, Mani Arun Vignesh, Sumanth C Raman, Arun Jijo, Bhavadharini Balaji, Nico Steckhan, Lena Maria Klara Roth, Moneeza K Siddiqui, Saravanan Jebarani, Ranjit Unnikrishnan, Viswanathan Mohan, Ranjit Mohan Anjana

“…Its performance was compared with an algorithm determined based on conditional pre-determined cut-offs and weights for each clinical feature [age at diagnosis, BMI, waist, HbA1c, Serum Triglycerides, HDL-Cholesterol, (C-peptide fasting, C-peptide stimulated) - optional. …”
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Reinforcement learning-based assimilation of the WOFOST crop model by Haochong Chen, Xiangning Yuan, Jian Kang, Danni Yang, Tianyi Yang, Xiang Ao, Sien Li

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Concrete Crack Detection and Segregation: A Feature Fusion, Crack Isolation, and Explainable AI-Based Approach by Reshma Ahmed Swarna, Muhammad Minoar Hossain, Mst. Rokeya Khatun, Mohammad Motiur Rahman, Arslan Munir

“…To isolate and quantify the crack region, this research combines image thresholding, morphological operations, and contour detection with the convex hulls method and forms a novel algorithm. …”
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