Enhanced safety assessment on tunnel excavation via refined rock mass parameter identification by Hongwei Huang, Tongjun Yang, Jiayao Chen, Zhongkai Huang, Chen Wu, Jianhong Man

“…The study provides significant insights into the intelligent evaluation of safety for continuous tunnel excavation.…”
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Deciphering the Social Vulnerability of Landslides Using the Coefficient of Variation-Kullback-Leibler-TOPSIS at an Administrative Village Scale by Yueyue Wang, Xueling Wu, Guo Lin, Bo Peng

“…Finally, the accuracy of the evaluation results is validated by applying the losses incurred from landslide disasters per unit area within the same year. …”
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Potential cost-savings of breastfeeding promotion to prevent breast cancer: a Monte Carlo simulation by Lai Ling Hui, Emily Liao, Jin Xiao Lian, Ching So, Ting Ting Wu, Carlos K. H. Wong, Tharani Loganathan, Edmund Anthony S. Nelson

“…Our study aimed to estimate the healthcare cost-savings resulting from a reduction in breast cancer attributed to an increase in the breastfeeding rate in Hong Kong. Methods This is an economic evaluation. We constructed an individual-based Monte Carlo method to simulate with probabilistic sensitivity analysis the development of breast cancer over a woman’s lifetime in a hypothetical birth cohort aged 20 years in 2018 (n = 33500) using best available data mainly from government statistics. …”
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Study Protocol: Evaluation of AI-Driven Grading Compared to Manual Grading in Predicting Embryo Viability and Successful Implantation and Clinical Pregnancy Outcomes in IVF Using S... by Puja Dhamija, Akash More, Namrata Choudhary, Tejaswini Wadhe, Devanshi R. Shah

“…Further research is needed to incorporate other embryonic developmental stages for a more comprehensive evaluation process.…”
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Evaluation of left atrial strain using speckle-tracking echocardiography to predict postoperative atrial fibrillation after coronary artery bypass grafting: a systematic review and... by E. Z. Golukhova, N. I. Bulaeva, D. V. Mrikaev, S. A. Aleksandrova, E. N. Kudryashova, D. Kh. Dzhidzalova, D. D. Mollaeva, B. Sh. Berdibekov

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Predictive power of selection tests on the academic performance of medical students by María E. Calles Santoyo, Raúl De León Escobedo, Ricardo Salas Flores, Brian González Pérez, Erick E. Hernández Molina

“…This study analyzes the predictive power of various selection tests for admission to the bachelor’s degree in medical surgery at the Autonomous University of Tamaulipas. …”
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Comparative Analysis of Machine Learning Methods with Chaotic AdaBoost and Logistic Mapping for Real-Time Sensor Fusion in Autonomous Vehicles: Enhancing Speed and Acceleration Pre... by Mehmet Bilban, Onur İnan

“…We introduce Chaotic AdaBoost (CAB), an advanced variant of AdaBoost that integrates a logistic chaotic map into its weight update process, overcoming the limitations of deterministic ensemble methods. CAB is evaluated alongside k-Nearest Neighbors (kNNs), Artificial Neural Networks (ANNs), standard AdaBoost (AB), Gradient Boosting (GBa), and Random Forest (RF) for speed and acceleration prediction using CARLA simulator data. …”
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School Context as a Predictor of Student Success in Mathematics by Dragana Radenović, Radovan Antonijević, Daliborka Popović, Fadilj Eminović, Kristina Ivanović

“…In this sense, the goal of the research is to determine the characteristics of the connection between student success in Mathematics and some factors of the school context (teaching planning, application of teaching methods and forms of work, teaching aids, different learning techniques and teaching models, evaluation and student progress). …”
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Evaluation of deep learning and convolutional neural network algorithms accuracy for detecting and predicting anatomical landmarks on 2D lateral cephalometric images: A systematic... by Jimmy Londono, Shohreh Ghasemi, Altaf Hussain Shah, Amir Fahimipour, Niloofar Ghadimi, Sara Hashemi, Zohaib Khurshid, Mahmood Dashti

“…ML-based cephalometric imaging reduces errors, improves accuracy, and saves time. Method: In this study, we conducted a meta-analysis and systematic review to evaluate the accuracy of ML software for detecting and predicting anatomical landmarks on two-dimensional (2D) lateral cephalometric images. …”
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Studies on Submersible Short-Circuit Blowing Based on Orthogonal Experiments, Back Propagation Neural Network Prediction, and Pearson Correlation Analysis by Xiguang He, Bin Huang, Likun Peng, Jia Chen

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In vivo evaluation of focused ultrasound ablation surgery (FUAS)-induced coagulation using echo amplitudes of the therapeutic focused ultrasound transducer by Yufeng Zhou, Xiaobo Gong, Yaqing You

“…To further evaluate its coagulation prediction capabilities, in vivo experiments were carried out. …”
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The Impact of the SMOTE Method on Machine Learning and Ensemble Learning Performance Results in Addressing Class Imbalance in Data Used for Predicting Total Testosterone Deficiency... by Mehmet Kivrak, Ugur Avci, Hakki Uzun, Cuneyt Ardic

“…We used the SMOTE method for the class imbalance problem. Methods: This database contains 3397 patients for the assessment of testosterone deficiency. …”
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An AutoML-Powered Analysis Framework for Forest Fire Forecasting: Adapting to Climate Change Dynamics by Shuo Zhang, Mengya Pan

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Enhancing one-year mortality prediction in STEMI patients post-PCI: an interpretable machine learning model with risk stratification by Wenqiang Li, Wenqiang Li, Dongdong Yan, Dongdong Yan, Dongdong Yan, Dongdong Yan, Wei Hu, Wei Hu, Wei Hu, Wei Hu, Xiaoling Su, Zheng Zhang, Zheng Zhang, Zheng Zhang, Zheng Zhang

“…Machine learning (ML) models have shown promise in predicting adverse clinical outcomes. However, a systematic approach that combines high predictive accuracy with model simplicity is still lacking.MethodsThis retrospective study applied three data processing and ML algorithms to address class imbalance and support model development. …”
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Stability evaluation of tunnels in steeply dipping layered rock mass using numerical models: a case study by Eleyas Assefa, Kidusyared Tilahun, Siraj Mulugeta Assefa, Nagessa Zerihun Jilo, Lysandros Pantelidis, Costas Sachpazis

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Effect of fracture energy estimation on the predictions of mode II behavior of bonded joints using cohesive zone models by Michele Perrella, Enrico Armentani, Giuseppe Lamanna, Valentino Paolo Berardi

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Effect of fracture energy estimation on the predictions of mode II behavior of bonded joints using cohesive zone models by Michele Perrella, Enrico Armentani, Giuseppe Lamanna, Valentino Paolo Berardi

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Digital Twin-Enabled Blockage-Aware Dynamic mmWave Multi-Hop V2X Communication by Supat Roongpraiwan, Zongdian Li, Tao Yu, Kei Sakaguchi

“…Leveraging this DT-enhanced architecture, we propose an advanced routing algorithm that combines high-precision environmental data with trajectory prediction to achieve blockage-aware mmWave multi-hop V2X routing. …”
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Radiological indicators and a novel combined predictive model for anticipating difficult laryngoscopy in cervical spondylosis patients: a prospective cohort study by Jiao Li, Yang Tian, Mingya Wang, Jingchao Fang, Hua Zhang, Feng Yue, Mao Xu, Jun Wang, Min Li, Xiangyang Guo, Yongzheng Han

“…A binary logistic regression model was developed to identify independent predictive factors. The predictive value of the indicators was evaluated with the area under the curve (AUC). …”
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Enhanced Prediction and Uncertainty Modeling of Pavement Roughness Using Machine Learning and Conformal Prediction by Sadegh Ghavami, Hamed Naseri, Farzad Safi Jahanshahi

“…This study aimed to develop an accurate IRI prediction model. Ten prediction methods were trained on a dataset of 35 independent variables. …”
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