Integrated Single-Cell and Spatial Transcriptomic Analysis Identifies ISR-Related Genes Driving Immune Regulation in Parkinson’s Disease by Jiang H, Zhang X, Feng S, Feng W

“…Further experiments in cell and mouse models confirmed that DDIT4 is highly expressed in PD, and reducing its levels helped protect nerve cells. …”
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Enhancing decision-making on detractor-causing failures: an approach combining data mining and machine learning by Yuri A. V. da Silva, Geraldo Cardoso de Oliveira Neto, Gustavo Lima, Sidnei A. de Araújo, Rodrigo Neri Bueno da Silva, Francisco Elanio Bezerra, Marlene Amorim

“…Based on these findings, targeted action plans were developed to support continuous improvement and operational effectiveness. This research advances the state of the art by introducing an explainable AI model capable of identifying the most impactful failures affecting customer satisfaction in large-scale retail operations. …”
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A SAR-based flood mapping approach: application of SAR-SIFT registration and modified DeepLabV3 segmentation in flood hazard assessment by Zhuoyu Zhang, Jiaqi Xiong, Xiang Li, Yu Li, Junrong Liu

“…By combining advanced georegistration, terrain-adaptive algorithms, and multi-source data fusion, this solution strengthens disaster response capabilities, offering robust real-time flood mapping and early warning systems for improved emergency management.…”
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ML-Based Self-Optimization Handover Technique for Beyond 5G Mobile Network by Saddam Alraih, Rosdiadee Nordin, Asma Abu-Samah, Ibraheem Shayea, Nor Fadzilah Abdullah

“…The results demonstrate that ML-SOHOT enhanced the HO optimization performance significantly and surpassed the competitive algorithms. Furthermore, ML-SOHOT achieves an average HO performance improvement of up to 96% compared to competitive algorithms from the literature. …”
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Artificial Intelligence in Primary Malignant Bone Tumor Imaging: A Narrative Review by Platon S. Papageorgiou, Rafail Christodoulou, Panagiotis Korfiatis, Dimitra P. Papagelopoulos, Olympia Papakonstantinou, Nancy Pham, Amanda Woodward, Panayiotis J. Papagelopoulos

“…Innovative segmentation techniques and multimodal imaging models have further enhanced healthcare efficiency by reducing physician workload and improving diagnostic accuracy. …”
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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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A Two-Stage Corrosion Defect Detection Method for Substation Equipment Based on Object Detection and Semantic Segmentation by Zhigao Wang, Xinsheng Lan, Yong Zhou, Fangqiang Wang, Mei Wang, Yang Chen, Guoliang Zhou, Qing Hu

“…These findings also validate the effectiveness of our data augmentation technique in enhancing the model’s detection accuracy for corrosion categories. …”
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Dual-Path Large Kernel Learning and Its Applications in Single-Image Super-Resolution by Zhen Su, Mang Sun, He Jiang, Xiang Ma, Rui Zhang, Chen Lv, Qiqi Kou, Deqiang Cheng

“…To enhance the performance of super-resolution models, neural networks frequently employ module stacking. …”
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Elevated Temperature Effects on FRP–Concrete Bond Behavior: A Comprehensive Review and Machine Learning-Based Bond Strength Prediction by Aseel Salameh, Rami Hawileh, Hussam Safieh, Maha Assad, Jamal Abdalla

“…Because of their improved properties, FRP composites are vastly used in the strengthening of aged concrete infrastructures. …”
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Development of GUI-Driven AI Deep Learning Platform for Predicting Warpage Behavior of Fan-Out Wafer-Level Packaging by Ching-Feng Yu, Jr-Wei Peng, Chih-Cheng Hsiao, Chin-Hung Wang, Wei-Chung Lo

“…Traditional electronic engineers often face difficulties in implementing AI-driven models due to the specialized programming and algorithmic expertise required. …”
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Optimizing Energy Efficiency in UPA-Assisted SWIPT Massive MIMO Systems Over Rician Fading Channels by Mohammad Hassan Adeli, Dariush Abbasi-Moghadam, Hossein Fotouhi, S. Mohammad Razavizadeh

“…Results demonstrate the superiority of our proposed design compared to the conventional scenarios with equal power allocation and fixed PS ratio algorithms with about 2 to 5 times EE improvements. …”
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A Novel Self-Attention-Enabled Weighted Ensemble-Based Convolutional Neural Network Framework for Distributed Denial of Service Attack Classification by Shravan Venkatraman, S. Kanthimathi, K. S. Jayasankar, T. Pranay Jiljith, R. Jashwanth

“…This innovative approach addresses critical limitations in current models and advances the state of the art in network security.…”
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Predictive Study on the Cutting Energy Efficiency of Dredgers Based on Specific Cutting Energy by Junlang Yuan, Ke Yang, Taiwei Yang, Haoran Xu, Ting Xiong, Shidong Fan

“…Based on the machine learning framework, a model framework for predicting the specific cutting energy according to the relevant parameters of the suction-lifting system is constructed. …”
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Energy-Efficient Target Area Imaging for UAV-SAR-Based ISAC: Beamforming Design and Trajectory Optimization by Jiayi Zhou, Xiangyin Zhang, Kaiyu Qin, Feng Yang, Libo Wang, Deyu Song

“…Numerical results demonstrate that compared to existing benchmarks and PSO algorithms, the proposed method significantly improves the energy efficiency of UAV-SAR-based ISAC systems through optimized trajectory design.…”
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A Machine Learning-Based Intelligent Framework for Predicting Energy Efficiency in Next-Generation Residential Buildings by Hafiz Muhammad Shakeel, Shamaila Iram, Richard Hill, Hafiz Muhammad Athar Farid, Akbar Sheikh-Akbari, Farrukh Saleem

“…Further, machine learning models revealed that Random Forest, Gradient Boosting, XGBoost, and LightGBM deliver the lowest mean square error scores of 6.305, 6.023, 7.733, 5.477, and 5.575, respectively, and demonstrated the effectiveness of advanced algorithms in forecasting energy performance. …”
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Artificial Intelligence-based Approaches for Characterizing Plaque Components From Intravascular Optical Coherence Tomography Imaging: Integration Into Clinical Decision Support Sy... by Michela Sperti, Camilla Cardaci, Francesco Bruno, Syed Taimoor Hussain Shah, Konstantinos Panagiotopoulos, Karim Kassem, Giuseppe De Nisco, Umberto Morbiducci, Raffaele Piccolo, Francesco Burzotta, Fabrizio D’Ascenzo, Marco Agostino Deriu, Claudio Chiastra

“…Deep learning models, particularly convolutional neural networks, further improve performance by enabling automatic feature extraction. …”
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Machine Learning-Driven GLCM Analysis of Structural MRI for Alzheimer’s Disease Diagnosis by Maria João Oliveira, Pedro Ribeiro, Pedro Miguel Rodrigues

“…Results: The cML algorithms achieved the following classification <i>accuracy</i>: 85.2% for <i>AD</i> vs. …”
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Dunes Identification Based on Attention Mechanism With Dual-Branch Codec by Zhaobin Wang, Yan Li, Yue Shi, Yaonan Zhang, Xuejun Guo

“…Specific work contents are as follows: A dual-branch codec dune morphological type segmentation model based on attention mechanism is proposed. In the dual-branch structure, the overcomplete and incomplete networks can take into account both small and large receptive fields, improving the situation of local detail loss caused by the incomplete network in the traditional semantic segmentation structure. …”
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Dual-stream interactive mechanism with multi-modal hierarchical aggregation transformer for gait recognition by Jinghang Liu, Xiangyuan Xu, Yan Qiu, Chunzhi Wang

“…This architecture not only adaptively modulates cross-modal feature importance but also enhances model robustness in complex scenarios. Comprehensive evaluations demonstrate that GaitSMAT achieves state-of-the-art (SOTA) performance on multiple public datasets (GREW, Gait3D, and SUSTech1K), exhibiting significant improvements over existing approaches. …”
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Elevating Patient Care With Deep Learning: High-Resolution Cervical Auscultation Signals for Swallowing Kinematic Analysis in Nasogastric Tube Patients by Farnaz Khodami, Amanda S. Mahoney, James L. Coyle, Ervin Sejdic

“…By applying established algorithms to an unseen population, we demonstrated the utility of HRCA signals for swallowing assessment in individuals with NG tubes and showcased the generalizability of algorithms developed in our previous studies. …”
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