Design, optimization, and validation of a magnetic mother-child robot system for targeted drug delivery by Bentao Zou, Huibin Liu, Xuehao Fen, Zhizheng Gao, Zhixing Ge, Wenguang Yang

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Building Change Detection Network Based on Multilevel Geometric Representation Optimization Using Frame Fields by Fachuan He, Hao Chen, Shuting Yang, Zhixiang Guo

“…By learning the local orientation information of the building structure, the frame field can effectively capture the geometric features of complex building features. During the training process, a multi-task learning strategy is used to align the predicted frame field with the real building outline, while learning the overall segmentation, edge outline, and corner point features of the building. …”
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Coordinated Optimization of Active and Reactive Power of Active Distribution Network Based on Safety Reinforcement Learning by Hao JIAO, Yanyan YIN, Chen WU, Jian LIU, Chunlei XU, Xian XU, Guoqiang SUN

“…A safe reinforcement learning method based on offline strategies is proposed. Through offline training of a large amount of historical operating data of the distribution network, it gets rid of the traditional optimization method. …”
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Optimizing Automated Hematoma Expansion Classification from Baseline and Follow-Up Head Computed Tomography by Anh T. Tran, Dmitriy Desser, Tal Zeevi, Gaby Abou Karam, Julia Zietz, Andrea Dell’Orco, Min-Chiun Chen, Ajay Malhotra, Adnan I. Qureshi, Santosh B. Murthy, Shahram Majidi, Guido J. Falcone, Kevin N. Sheth, Jawed Nawabi, Seyedmehdi Payabvash

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The contribution of personalized video feedback to robotic partial nephrectomy training in realistic 3D tumor kidney models: design, production and implementation by Ahmet Furkan Sarıkaya, Kayhan Tarım, Ersin Köseoğlu, Arif Özkan, İbrahim Can Aykanat, Baris Esen, Umut Can Karaarslan, Mustafa Müdüroğlu, Şevval Kanlı, Murat Can Kiremit, Yakup Kordan, Mevlana Derya Balbay, Tarık Esen, Serdar Aydın, Serdar Aydın, Abdullah Erdem Canda, Abdullah Erdem Canda

“…These findings support the use of patient-specific 3D models and targeted feedback as cost-effective and scalable strategies to optimize surgical education and shorten the learning curve for complex procedures.…”
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Optimizing Vital Signs in Patients With Traumatic Brain Injury: Reinforcement Learning Algorithm Development and Validation by Hongwei Zhang, Mengyuan Diao, Sheng Zhang, Peifeng Ni, Weidong Zhang, Chenxi Wu, Ying Zhu, Wei Hu

“… Abstract BackgroundTraumatic brain injury (TBI) is a critically ill disease with a high mortality rate, and clinical treatment is committed to continuously optimizing treatment strategies to improve survival rates. …”
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Non-Contact Oxygen Saturation Estimation Using Deep Learning Ensemble Models and Bayesian Optimization by Andrés Escobedo-Gordillo, Jorge Brieva, Ernesto Moya-Albor

“…Thus, by leveraging Bayesian optimization for hyperparameter tuning and integrating a Bagging Ensemble, we achieved a significant reduction in the training error (bias), achieving a better generalization over the test set, and reducing the variance in comparison with the baseline model for SpO₂ estimation.…”
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The machine learning algorithm based on decision tree optimization for pattern recognition in track and field sports. by Guomei Cui, Chuanjun Wang

“…This study aims to solve the problems of insufficient accuracy and low efficiency of the existing methods in sprint pattern recognition to optimize the training and competition strategies of athletes. …”
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An Empirical Comparison of Urban Road Travel Time Prediction Methods—Deep Learning, Ensemble Strategies and Performance Evaluation by Yizhe Wang, Yangdong Liu, Xiaoguang Yang

“…This study compares the predictive performance of deep learning methods with traditional shallow learning methods for urban road travel time prediction, and explores the potential for improving prediction effectiveness through multi-run training strategies for hyperparameter optimization and ensemble learning. …”
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Sample Denoising and Optimization Technique Based on Noise Filtering and Evolutionary Algorithms for Imbalanced Data Classification by Fhira Nhita, Asniar, Isman Kurniawan, Adiwijaya

“…Therefore, the data preprocessing strategy at the before and after data balancing process is crucial to improve data quality before the classification process is conducted. …”
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Optimizing MRI Scheduling in High-Complexity Hospitals: A Digital Twin and Reinforcement Learning Approach by Fabián Silva-Aravena, Jenny Morales, Manoj Jayabalan, Paula Sáez

“…Addressing these challenges requires intelligent scheduling strategies capable of dynamically managing patient waitlists based on clinical urgency while optimizing resource allocation. …”
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Research on intelligent energy management strategies for connected range-extended electric vehicles based on multi-source information by Xuewen Zhai, Hanwu Liu, Wencai Sun, Zihang Su

“…To achieve the application of multi-source traffic information and enhance the timeliness in multi-objective optimization (MOO) for connected automated range-extended electric vehicles (CAR-EEV), this paper proposes an intelligent energy management strategy (EMS) from a multi-objective perspective. …”
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Epigenetic modulation by life–style: advances in diet, exercise, and mindfulness for disease prevention and health optimization by José Ostaiza-Cardenas, Andrea C. Tobar, Stefany Carolina Costa, Diana Sofia Calero, Alisson López-Carrera, Fátima German Bermúdez, Fátima German Bermúdez, Andrea Orellana-Manzano, Andrea Orellana-Manzano

“…However, more research is needed to understand the long-term effects of lifestyle factors on epigenetics and to develop personalized strategies that optimize disease prevention and overall wellbeing.…”
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Quantum-enhanced beetle swarm optimized ELM for high-dimensional smart grid intrusion detection by Na Cheng, Shuqing Wang, Lihong Zhao, Yan Hu

“…By integrating quantum-enhanced optimization strategies, QBOA-ELM demonstrates superior performance across multiple aspects. …”
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Effects of Exercise on Post-Stroke Depression: A Systematic Review and Meta-Analysis of Randomized Controlled Trials by Yifan Zhang, Gen Li, Wenda Zheng, Ze Xu, Yuanyuan Lv, Xiaojie Liu, Laikang Yu

“…Exercise represents an effective strategy for managing PSD, with multicomponent training potentially serving as the optimal intervention. …”
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ZooCNN: A Zero-Order Optimized Convolutional Neural Network for Pneumonia Classification Using Chest Radiographs by Saravana Kumar Ganesan, Parthasarathy Velusamy, Santhosh Rajendran, Ranjithkumar Sakthivel, Manikandan Bose, Baskaran Stephen Inbaraj

“…The model was trained, tested, and validated on the Kaggle CXR Images (Pneumonia) dataset. …”
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Simulation-Based Schedule Optimization for Virtual Coupling-Enabled Rail Transit Services with Multiagent Technique by Jiamin Zhang

“…With the aim of optimizing the interdeparture train headway time, providing the variable capacity for diverse passenger demand, maximizing the passenger riding comfort degree, and minimizing passenger travel cost and train operation cost, the dynamic schedule for VC-enabled rail transit services is investigated with the multiagent simulation technique on NetLogo platform. …”
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Optimizing In-Bed Posture Classification Using Tanh-Activated Kolmogorov–Arnold Networks (Tanh-KAN) by Weiwei Chen, Bing Zhou, Wai Yie Leong

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Optimization of sports injury treatment through artificial intelligence: Methods for effective prevention, diagnosis and rehabilitation by Kimi Milić Marko, Sinanović Šćepan, Jestrović Vladimir

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Comparison of LSTM and Transformer Models in Predicting NVIDIA Stock Closing Prices and the Application of Rule-based Trading Strategies by Muhammad Irfan Abdul Gani, Putry Wahyu Setyaningsih

“…Gaussian noise augmentation was applied during training to improve model generalization. This study also explores investment strategy development by analyzing rule-based trading signals, generating buy (long) and sell (short) signals based on predicted price movements. …”
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