A Method of Intelligent Driving-Style Recognition Using Natural Driving Data by Siyang Zhang, Zherui Zhang, Chi Zhao

“…Identifying diverse driving styles and corresponding types is crucial for providing targeted training and assistance to drivers, enhancing safety awareness, optimizing driving costs, and improving autonomous driving systems responses. …”
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A novel canopy water indicator for UAV imaging to monitor winter wheat water status by Meiyan Shu, Zhenghang Ge, Yang Li, Jibo Yue, Wei Guo, Yuanyuan Fu, Ping Dong, Hongbo Qiao, Xiaohe Gu

“…However, the complexity involved in acquiring LAI data and the associated high costs limit the practical application of FMCc in crop water monitoring. …”
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Prediction of permeability and effective porosity values using ANN in Maleh field by Mohammed Essa Nassani, Ali Alaji

“…The ANN was tested on independent data and demonstrated exceptional performance, achieving 96% accuracy for effective porosity and 98% for permeability predictions in sandstone formations. This efficient algorithm eliminates the need for core sample analysis, reducing costs and time while improving prediction reliability, making it a valuable tool for subsurface characterization and resource exploration.…”
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Robust vector-weighted and matrix-weighted multi-view hard c-means clustering by Zhe Liu, Sarah Aljohani, Sijia Zhu, Tapan Senapati, Gözde Ulutagay, Salma Haque, Nabil Mlaiki

“…With the rapid advancement of information technology, multi-view data has become ubiquitous, prompting extensive attention towards multi-view clustering algorithms. Despite significant strides, several challenges persist: (1) the prevalence of noise and outliers in real-world multi-view data often compromises the efficacy of clustering; (2) most existing multi-view clustering algorithms predominantly assess the overall contribution of each view, while neglecting the intra-view contributions. …”
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Human-machine co-adaptation to automated insulin delivery: a randomised clinical trial using digital twin technology by Boris P. Kovatchev, Patricio Colmegna, Jacopo Pavan, Jenny L. Diaz Castañeda, Maria F. Villa-Tamayo, Chaitanya L. K. Koravi, Giulio Santini, Carlene Alix, Meaghan Stumpf, Sue A. Brown

“…Abstract Most automated insulin delivery (AID) algorithms do not adapt to the changing physiology of their users, and none provide interactive means for user adaptation to the actions of AID. …”
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Development and evaluation of a machine learning model for post-surgical acute kidney injury in active infective endocarditis by XinPei Liu, SanXi Ai, RuiMing Yu, ChaoJi Zhang, Qi Miao

“…LASSO regression identified 25 significant features for the models. Among the six algorithms tested, the radial basis function support vector machine (RBF-SVM) had the highest AUC at 0.771. …”
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EPIGENETIC REGULATION OF GENE EXPRESSION IN HEAD AND NECK SQUAMOUS CELL CARCINOMA: THERAPEUTIC PERSPECTIVES by R. B. Samsonov, Z. A. Radzhabova, Yu. V. Cheburkin, V. A. Klyuge, E. V. Tkachenko, A. V. Malek

“…Despite the fact that tumors of head and neck are generally available for visual inspection, about 60–70 % of the patients are diagnosed with it at advanced (III or IV) stages of the disease. Unfortunately, optimization of diagnostic algorithms and wide implementation of instrumental diagnostics (ultrasound examination, computed tomography, fiber endoscopy) do not improve the situation. …”
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Explainable Machine Learning Models for Colorectal Cancer Prediction Using Clinical Laboratory Data by Rui Li MS, Xiaoyan Hao MS, Yanjun Diao MD, Liu Yang MS, Jiayun Liu MD

“…Incorporating stool miR-92a detection into the model further improved diagnostic performance. Shapley additive explanations (SHAP) plots indicated that FOBT, CEA, lymphocyte percentage (LYMPH%), and hematocrit (HCT) were the most significant features contributing to CRC diagnosis. …”
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Application of machine learning for predicting the incubation period of water droplet erosion in metals by Khaled AlHammad, Mamoun Medraj, Moussa Tembely

“…Hyperparameter optimization techniques showed minimal improvement in model performance, suggesting that the transformations effectively captured the underlying relationships in the data. …”
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Comparative effect of traditional and collaborative watershed management approaches on flood components by Ali Nasiri Khiavi, Mehdi Vafakhah, Seyed Hamidreza Sadeghi, Changhyun Jun, Sayed M. Bateni

“…Abstract Identifying the critical areas of flood generation and determining the optimal measures for flood control and management (FCM) is one of the most important basics of watershed management. …”
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Expansion Planning of Electrical Distribution Systems Considering Voltage Quality and Reliability Criteria by Marco Israel Zuñiga Villarreal, Alexander Aguila Téllez, Narayanan Krishnan, Marcelo García

“…The proposed algorithm recommended upgrades to electrical conductors without significantly affecting the system costs. …”
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Emerging trends in sustainable energy system assessments: integration of machine learning with techno-economic analysis and lifecycle assessment by Ebrahimpourboura Zahra, Mosalpuri Manish, Jonas Baltrusaitis, Dubey Pallavi, Mba Wright Mark

“…Key case studies demonstrate the transformative potential of ML in improving economic viability and environmental sustainability, highlighting its role in predicting system performance, optimizing configurations, and reducing costs and impacts. …”
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A novel biochemical analysis for ApoE4 quantification in plasma and discrimination of homozygous and heterozygous APOE ε4 carriers by Andrés Rodríguez, Olga Calero, Sergio Veiga, Miriam Menacho-Román, Ignacio Arribas, Lluís Cano, Guillermo García-Ribas, Miguel Calero

“…Discussion The e4Quant assay offers a rapid, cost-effective, and highly accurate biochemical alternative to APOE genotyping, suitable for clinical and research settings, particularly in assessing AD risk and optimizing anti-amyloid therapeutic strategies. …”
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Enhancing grid-connected PV-EV charging station performance through a real-time dynamic power management using model predictive control by Aziz Watil, Hamid Chojaa

“…It also provides flexibility in BEV power sizing, optimizing the use of power electronics converters to reduce costs and complexity. …”
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Soil Organic Carbon Prediction and Mapping in Morocco Using PRISMA Hyperspectral Imagery and Meta-Learner Model by Yassine Bouslihim, Abdelkrim Bouasria, Budiman Minasny, Fabio Castaldi, Andree Mentho Nenkam, Ali El Battay, Abdelghani Chehbouni

“…This study presents a novel meta-learner framework that combines multiple machine learning algorithms and spectra processing algorithms to optimize SOC prediction using the PRISMA hyperspectral satellite imagery in the Doukkala plain of Morocco. …”
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FPA-based weighted average ensemble of deep learning models for classification of lung cancer using CT scan images by Liang Zhou, Achin Jain, Arun Kumar Dubey, Sunil K. Singh, Neha Gupta, Arvind Panwar, Sudhakar Kumar, Turki A. Althaqafi, Varsha Arya, Wadee Alhalabi, Brij B. Gupta

“…Abstract Cancer is among the most dangerous diseases contributing to rising global mortality rates. …”
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Automated Alerts Systems for Pediatric Sepsis Patients: A Systematic Review by Mahmasoni Masdar, Ariani Arista Putri Pertiwi, Tiara Royani, Nana Caterina Sandi, Muhammad Ulin Nuha, Fransiska Regina Cealy, Alessandra Hernanda Soselisa, Suprihatiningsih Suprihatiningsih, Desi Dwi Siwi Atika Dewi

“…Limitations include language restrictions and the inability to assess each tool's effectiveness or identify the optimal sepsis detection algorithm, underscoring the need for further research, including a meta-analysis.…”
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Experimental Study on the Unsteady Characteristics and the Impact Performance of a High-Pressure Submerged Cavitation Jet by Yongfei Yang, Wei Li, Weidong Shi, Ling Zhou, Wenquan Zhang

“…The impact load of the cavitation jet is mainly affected by the stand-off distance of the nozzle from the impinged target, while the nozzle outlet geometry also has an effect on the impact performance. Optimizing the stand-off distance and the outlet geometry of the nozzles is found to be a good way to improve the performance of the cavitation jet.…”
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Association of MTHFR Polymorphisms with H-Type Hypertension: A Systemic Review and Network Meta-Analysis of Diagnostic Test Accuracy by Yixuan Kong, Jinghui Zheng, Lijuan Li, Liying Lu, Jie Wang

“…A network meta-analysis of diagnostic test and Thakkinstian’s algorithm were used to select the most appropriate genetic model, along with false-positive report probability (FPRP) for noteworthy associations. …”
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SiCRNN: A Siamese Approach for Sleep Apnea Identification via Tracheal Microphone Signals by Davide Lillini, Carlo Aironi, Lucia Migliorelli, Leonardo Gabrielli, Stefano Squartini

“…The final detection of <i>apnea</i> events is performed using an unsupervised clustering algorithm, specifically <i>k-means</i>. Multiple experimental runs were carried out to determine the optimal network configuration and the most suitable type and frequency range for the input data. …”
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