Prediction of Myocardial Infarction Based on Non-ECG Sleep Data Combined With Domain Knowledge by Changyun Li, Yonghan Zhao, Qihui Mo, Zhibing Wang, Xi Xu

“…The experiments demonstrate that the model’s accuracy reaches its optimal level by combining the age rule, improving to 73.1%. …”
Get full text

Degree-Constrained k-Minimum Spanning Tree Problem by Pablo Adasme, Ali Dehghan Firoozabadi

“…Our numerical results indicate that the proposed models and algorithms allow obtaining optimal and near-optimal solutions, respectively. …”
Get full text

Unveiling nature's secrets: Deep learning for enhanced biogenic emission resolution by Antonio Giganti

“…Consequently, many existing BVOC emission maps may not be fully suitable for reliable atmospheric, climate, and forecasting model simulations.My research aims to explore and assess the use of novel AI-based algorithms to improve the spatiotemporal modeling of BVOC emissions. …”
Get full text

A SAC-Bi-RRT Two-Layer Real-Time Motion Planning Approach for Robot Assembly Tasks in Unstructured Environments by Qinglei Zhang, Siyao Hu, Jianguo Duan, Jiyun Qin, Ying Zhou

“…To realize the safe assembly of assembly robots in dynamic and complex environments, a dynamic obstacle avoidance trajectory planning method for robots combining traditional planning algorithms and deep reinforcement learning algorithms is proposed to improve the robot’s agent and obstacle avoidance ability in dynamic and complex environments. …”
Get full text

Innovative Lightweight Detection for Airborne Remote Sensing: Integrating G-Shuffle and Dynamic Multiscale Pyramid Networks by Ruofei Liang, Yigang Cen, Linna Zhang, Fugui Zhang, Yansen Huang, Fei Gan

“…To address the challenges of significant scale variations and difficulty in extracting discriminative features for small targets in airborne remote sensing object detection, while considering the constraints and efficiency requirements of onboard systems, this article proposes a lightweight detection algorithm. First, a structural reparameterization strategy is applied to optimize depthwise separable convolutions, simplifying complex structures during the inference stage, which improves inference speed and memory utilization. …”
Get full text

State-of-the-Art on IoV-Based Deep Learning Framework for Enhanced Driving Behavior Recognition: Recent Progress, Technology Updates, Challenges, and Future Direction by Hongguang Li, Shafrida Sahrani, Mahidur R. Sarker, Yinglin Xiao

“…Therefore, this paper proposes an active IoV based DL framework, emphasizing the feasibility of enhancing data processing techniques and algorithmic improvements to boost model accuracy and generalization ability, and highlighting the potential of integrating edge and cloud computing to support real-time data analysis and decision-making. …”
Get full text

Breeding of Solanaceous Crops Using AI: Machine Learning and Deep Learning Approaches—A Critical Review by Maria Gerakari, Anastasios Katsileros, Konstantina Kleftogianni, Eleni Tani, Penelope J. Bebeli, Vasileios Papasotiropoulos

“…Through advanced algorithms and predictive models, ML and DL facilitate the identification and optimization of key traits, including higher yield, improved quality, pest resistance, and tolerance to extreme climatic conditions. …”
Get full text

Research and application of mining AI video edge computing technology by ZHANG Liya, HAO Bonan, MA Zheng, YANG Zhifang

“…A lightweight software development kit (SDK) framework based on the register machine was proposed to decouple operators, improving the parallel computing ability of the algorithms and reducing the storage requirements of the SDK. …”
Get full text

Belief in building a full-fledged distance learning course in athletic training by Andrii Yefremenko, Illia Shutieiev

“…In particular, the experts mostly agreed with the logic and completeness of the course structure, the expediency of centralised content placement in the cloud environment, the optimality of the selected communication channels (email and cloud services), the clarity of the motor learning algorithm for remote performance by students, the adequacy of the proposed evaluation system and the presence of significant advantages in the use of tablets/smartphones in the educational process. …”
Get full text

Churn prediction for SaaS company with machine learning by Hugo Eduardo Sanches, Ayslan Trevizan Possebom, Linnyer Beatrys Ruiz Aylon

“…Design/methodology/approach – Through a preprocessing and normalization of data, seven machine learning algorithms were applied. The models were trained, and also cross-validation and parameter tuning techniques were applied to improve results. …”
Get full text

Enhancing action recognition in educational settings using AI-driven information systems for public health monitoring by Changchun Lu, Han Ruijuan

“…These limitations hinder their effectiveness, particularly in detecting health-related behaviors such as sedentary patterns, social interactions, and hygiene compliance.MethodsTo overcome these shortcomings, this research introduces an AI-driven information system that leverages advanced deep learning models and an Adaptive Knowledge Embedding Network (AKEN) to improve action recognition accuracy. …”
Get full text

Brachial Plexopathy in Head and Neck Cancer Potentially Related to LET-Dependent RBE by Abanob Hanna, Anthony Casper, Roi Dagan, Hardev S. Grewal, Jiyeon Park, Eric D. Brooks, Erik Traneus, Lars Glimelius, Perry B. Johnson, Mohammad Saki, Yawei Zhang, Twyla R. Willoughby, Julie A. Bradley, Jackson Browne, Mark E. Artz

“…Conservative treatment with pentoxifylline, gabapentin, and physical therapy improved his symptoms. (2) Methods: The original treatment plan was retrospectively analyzed using Monte Carlo dose algorithms and LET-dependent RBE models from McMahon and McNamara. …”
Get full text

Low-light image enhancement method based on retinex theory and dual-tree complex wavelet transform by Yuqian Zhang, Jie Jiang, Zhan Wang, Qi Zhang, Yudi Jiang, Jun Liu, Zeyao Hou

“…Although Vision Transformers (ViTs) excel at modeling non-local information, they inadequately perceive frequency information in low-light images, which is crucial for image enhancement. …”
Get full text

Parsimonious and explainable machine learning for predicting mortality in patients post hip fracture surgery by Fouad Trad, Bassel Isber, Ryan Yammine, Khaled Hatoum, Dana Obeid, Mohammad Chahine, Rachid Haidar, Ghada El-Hajj Fuleihan, Ali Chehab

“…In this study, we developed machine learning (ML) algorithms to estimate 30-day mortality risk post-hip fracture surgery in the elderly using data from the National Surgical Quality Improvement Program (NSQIP 2012–2017, n = 62,492 patients). …”
Get full text

Advancing soil mapping and management using geostatistics and integrated machine learning and remote sensing techniques: a synoptic review by Sunshine A. De Caires, Chaney St Martin, Melissa A. Atwell, Fuat Kaya, Glorious A. Wuddivira, Mark N. Wuddivira

“…Future research should focus on improving model accuracy, interpretability, transparency, and explainability. …”
Get full text

A human pose estimation network based on YOLOv8 framework with efficient multi-scale receptive field and expanded feature pyramid network by Shaobin Cai, Han Xu, Wanchen Cai, Yuchang Mo, Liansuo Wei

“…First, the EMRF module is employed to further enhance the model’s feature representation capability. Second, the EFPN optimizes cross-level information exchange and improves multi-scale data integration. …”
Get full text

Explainable Boosting Machines Identify Key Metabolomic Biomarkers in Rheumatoid Arthritis by Fatma Hilal Yagin, Cemil Colak, Abdulmohsen Algarni, Ali Algarni, Fahaid Al-Hashem, Luca Paolo Ardigò

“…EBM, LightGBM, and AdaBoost algorithms were applied to generate a discriminatory model between RA and controls. …”
Get full text

Disseminated intravascular coagulation by Satoshi Gando, Marcel Levi, Cheng-Hock Toh

“…Anticoagulant use has been extensively debated; however, the selection of optimal target patients could optimize their application and improve patient outcomes in the near future. …”
Get full text

Privacy-Preserving Hierarchical Reinforcement Learning Framework for Task Offloading in Low-Altitude Vehicular Fog Computing by Zhiwei Wei, Jingxin Mao, Bing Li, Rongqing Zhang

“…At the local DRL level, we design an Attention-enhanced Federated Proximal Policy Optimization (AFedPPO) algorithm to enable decentralized training and execution (DTDE) for task offloading, which is privacy-preserving, effective, and scalable for the low-altitude VFC systems. …”
Get full text

Characterization of immune microenvironment associated with medulloblastoma metastasis based on explainable machine learning by Fengmao Zhao, Xiangjun Liu, Jingang Gui, Hailang Sun, Nan Zhang, Yun Peng, Ming Ge, Wei Wang

“…Eight algorithms were evaluated, and the optimal model was selected. …”
Get full text