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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Exploring the effect of the triglyceride-glucose index on bone metabolism in prepubertal children, a retrospective study: insights from traditional methods and machine-learning-bas... by Shunshun Cao, Aolei Chen, Botian Song, Yangyang Hu

“…Bone turnover markers (BTMs) provide a non-invasive method for evaluating bone remodeling, but their relationship to obesity-related metabolic changes requires further study. …”
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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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Evaluating the impact of machine learning models on adult major depressive disorder using conventional treatment strategies: a systematic review approach by Nishant Yadav, Anamika Gulati, Varun Gulati, Prashant Yadav

“…However, methodology heterogeneity, varied sample sizes, and lack of external validation of these models limit their clinical use. Methods A comprehensive systematic review of 30 studies employing ML models for MDD treatment response prediction was conducted. …”
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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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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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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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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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Bridging Predictive Insights and Retention Strategies: The Role of Account Balance in Banking Churn Prediction by Tahsien Al-Quraishi, Osamah Albahri, Ahmed Albahri, Abdullah Alamoodi, Iman Mohammed Sharaf

“…The tested model set achieved its highest predictive performance by applying boosting methods. …”
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Study protocol for a triple-blind randomised controlled trial evaluating a machine learning-based predictive clinical decision support tool for internet-delivered cognitive behavio... by Pontus Bjurner, Nils Hentati Isacsson, Fehmi Ben Abdesslem, Magnus Boman, Erik Forsell, Viktor Kaldo

“…Methods and analysis: A triple blind RCT comparing ICBT with a DST (DST condition), to ICBT as usual (TAU condition). …”
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Development and Validation of a Predictive Model for Growth of Salmonella Infantis in Ground Turkey by Thomas P. Oscar

“…Data and tertiary model predictions were evaluated using the test data, model performance, and model validation criteria of the Acceptable Prediction Zones method in the Validation Software Tool. …”
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Prediction of absolute bioavailability of medicines in children: based on predicted pediatric clearance from adults by Iftekhar Mahmood

“…Aim: The objective of this study was to evaluate the predictive performance of a proposed method to predict absolute bioavailability of medicines in children (infants to adolescents). …”
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