Predicting 30-Day Venous Thromboembolism Following Total Joint Arthroplasty: Adjusting for Trends in Annual Length of Stay by Johnathan R. Lex, MBChB, MASc, Robert Koucheki, MD, MEng, Aazad Abbas, MD, Jesse I. Wolfstadt, MD, MSc, FRCSC, FAAOS, Alexander S. McLawhorn, MD, MBA, Bheeshma Ravi, MD, PhD, FRCSC

“…Development of more accurate machine learning models for VTE prediction may improve risk stratification, prevention, and monitoring for arthroplasty patients.…”
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Low-Light Image and Video Enhancement for More Robust Computer Vision Tasks: A Review by Mpilo M. Tatana, Mohohlo S. Tsoeu, Rito C. Maswanganyi

“…The review analyzes both traditional and deep learning-based enhancers and provides a comparative analysis on recent models in the field. The review also analyzes how popular computer vision tasks are improved and made more robust when coupled with light enhancement algorithms. …”
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InvarNet: Molecular property prediction via rotation invariant graph neural networks by Danyan Chen, Gaoxiang Duan, Dengbao Miao, Xiaoying Zheng, Yongxin Zhu

“…Recently, deep learning methods, particularly Graph Neural Networks (GNNs), have significantly improved efficiency by capturing molecular structures’ invariance under translation, rotation, and permutation. …”
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Fractional Optimizers for LSTM Networks in Financial Time Series Forecasting by Mustapha Ez-zaiym, Yassine Senhaji, Meriem Rachid, Karim El Moutaouakil, Vasile Palade

“…This novel approach leverages the memory-retentive properties of fractional calculus to improve convergence behavior and model efficiency. …”
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The PLSR-ML fusion strategy for high-accuracy leaf potassium inversion in karst region of Southwest China by Zhihao Song, Zhihao Song, Wen He, Yuefeng Yao, Ling Yu, Jinjun Huang, Yong Xu, Haoyu Wang

“…Validation coefficient of determination (R²) values reached 0.89, 0.94, and 0.96, respectively—representing improvements of 206%, 147%, and 108% over standalone algorithms. …”
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Intelligent Reflecting Surface-Assisted Wireless Communication Using RNNs: Comprehensive Insights by Rana Tabassum, Mohammad Abrar Shakil Sejan, Md Habibur Rahman, Md Abdul Aziz, Hyoung-Kyu Song

“…By adjusting the propagation environment using reconfigurable reflecting elements, intelligent reflecting surfaces (IRSs) have become potential techniques used to improve the efficiency of wireless communication networks. …”
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Preliminary study: Data analytics for predicting medication adherence in Malaysian arthritis patients by Firdaus Aziz, Shubathira Sooriamoorthy, Bryan Liew, Sharifah M. Syed Ahmad, Wei Wen Chong, Sorayya Malek, Adliah Mhd Ali

“…These variables were used to build predictive models for medication adherence. Results Results from machine learning algorithms showed varied performance. …”
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Integrating SEResNet101 and SE-VGG19 for advanced cervical lesion detection: a step forward in precision oncology by Yan Ye, Yuanyuan Chen, Jiajia Pan, Peipei Li, Feifei Ni, Haizhen He

“…Conclusion Our results indicate that SEResNet101 offers a promising enhancement over existing screening methods, integrating advanced deep learning algorithms to significantly improve the precision of cervical lesion classification. …”
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Quantum-inspired robust optimization for coordinated scheduling of PV-hydrogen microgrids under multi-dimensional uncertainties by Yunxiao Bai, Yu Sui, Xiaoyu Deng, Xiangbing Wang

“…These improvements reflect not only enhanced adaptability and computational efficiency, but also the practical feasibility of real-time learning in resilient energy scheduling. …”
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Longitudinal Digital Phenotyping of Multiple Sclerosis Severity Using Passively Sensed Behaviors and Ecological Momentary Assessments: Real-World Evaluation by Zongqi Xia, Prerna Chikersal, Shruthi Venkatesh, Elizabeth Walker, Anind K Dey, Mayank Goel

“…Among the best-performing models with the least sensor data requirement, the ML algorithm predicted depressive symptoms with an accuracy of 80.6% (F1-score=0.76), high global MS symptom burden with an accuracy of 77.3% (F1-score=0.78), severe fatigue with an accuracy of 73.8% (F1-score=0.74), and poor sleep quality with an accuracy of 72.0% (F1-score=0.70). …”
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Automated classification of stress and relaxation responses in major depressive disorder, panic disorder, and healthy participants via heart rate variability by Sangwon Byun, Ah Young Kim, Min-Sup Shin, Hong Jin Jeon, Hong Jin Jeon, Chul-Hyun Cho, Chul-Hyun Cho

“…This highlights the need for advanced stress-monitoring technologies to improve treatment. Stress affects the autonomic nervous system, which can be evaluated via heart rate variability (HRV). …”
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Committee Machine Learning for Electrofacies-Guided Well Placement and Oil Recovery Optimization by Adewale Amosu, Dung Bui, Oluwapelumi Oke, Abdul-Muaizz Koray, Emmanuel Appiah Kubi, Najmudeen Sibaweihi, William Ampomah

“…In this study, we develop a workflow that mitigates the variability in results produced by different clustering algorithms using a committee machine. Using several unsupervised machine learning methods, including k-means, k-median, hierarchical clustering, spectral clustering, and the Gaussian mixture model, we predict electrofacies from wireline well log data and generate their 3D vertical and lateral distributions and inferred geological properties. …”
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Individual Tree Segmentation Based on Region-Growing and Density-Guided Canopy 3-D Morphology Detection Using UAV LiDAR Data by Shihua Li, Shunda Zhao, Zhilin Tian, Hao Tang, Zhonghua Su

“…Currently, existing methods fail to fully utilize the height information, density information, and vertical structure details of tree crowns within point cloud data, resulting in complex algorithmic processes and reduced reliability. This study proposes a novel method that combines the canopy height model (CHM) and point cloud data for segmenting individual trees and employs height and density information for morphological detection of tree canopies. …”
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Ensemble deep learning and EfficientNet for accurate diagnosis of diabetic retinopathy by Lakshay Arora, Sunil K. Singh, Sudhakar Kumar, Hardik Gupta, Wadee Alhalabi, Varsha Arya, Shavi Bansal, Kwok Tai Chui, Brij B. Gupta

“…This framework takes help from the EfficientNet Machine Learning algorithms and employing advanced CNN layering techniques. …”
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Field Ridge Segmentation and Navigation Line Coordinate Extraction of Paddy Field Images Based on Machine Vision Fused with GNSS by Muhua Liu, Xulong Wu, Peng Fang, Wenyu Zhang, Xiongfei Chen, Runmao Zhao, Zhaopeng Liu

“…Finally, a homogeneous coordinate transformation method was used to extract the navigation line coordinates, with the model and algorithms deployed on the Jetson AGX Xavier platform Field tests demonstrated a real-time segmentation speed of 26.31 fps, pixel segmentation accuracy of 92.43%, and an average intersection ratio of 90.62%. …”
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Field measurement of atmospheric CO₂ column abundance based on portable laser heterodyne radiometer by Yong Wang, Yong Wang, Maolei Zhang, Maolei Zhang, Jiapeng Wang, Jiapeng Wang, Gang Wang, Gang Wang, Ruyue Cui, Ruyue Cui, Lei Dong, Lei Dong, Hongpeng Wu, Hongpeng Wu

“…Furthermore, a forward model based on line-by-line integration and an iterative fitting algorithm were employed to achieve high-precision CO₂ column abundance calculations. …”
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Anatomically Guided Deep Learning System for Right Internal Jugular Line (RIJL) Segmentation and Tip Localization in Chest X-Ray by Siyuan Wei, Liza Shrestha, Gabriel Melendez-Corres, Matthew S. Brown

“…To reduce the workload of clinicians, deep learning-based automated detection algorithms have been developed to detect CVCs in CXRs. …”
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Deciphering microbial and metabolic influences in gastrointestinal diseases-unveiling their roles in gastric cancer, colorectal cancer, and inflammatory bowel disease by Daryll Philip, Rebecca Hodgkiss, Swarnima Kollampallath Radhakrishnan, Akshat Sinha, Animesh Acharjee

“…These models were then employed for cross-disease analysis, revealing that models trained on GC data successfully predicted IBD biomarkers, while CRC models predicted GC biomarkers with optimal performance scores. …”
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Role of Roadside Units in Cluster Head Election and Coverage Maximization for Vehicle Emergency Services by Ravneet Kaur, Robin Doss, Lei Pan, Chaitanya Singla, Selvarajah Thuseethan

“…Efficient clustering algorithms are critical for enabling the timely dissemination of emergency messages across maximum coverage areas in vehicular networks. …”
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Post-Quantum Cryptography Resilience in Telehealth Using Quantum Key Distribution by Don Roosan, Rubayat Khan, Saif Nirzhor, Fahmida Hai

“…Despite increased computational overhead, the DAG approach efficiently handled parallel transactions, indicating improved scalability compared to traditional linear blockchains. …”
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