Machine learning allows robust classification of lung neoplasm tissue using an electronic biopsy through minimally-invasive electrical impedance spectroscopy by Georgina Company-Se, Virginia Pajares, Albert Rafecas-Codern, Pere J. Riu, Javier Rosell-Ferrer, Ramon Bragós, Lexa Nescolarde

“…This study aims to use classification algorithms with minimally invasive electrical impedance spectroscopy to improve neoplastic lung tissue identification during biopsies. …”
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Swarm intelligence for energy-efficient heating, ventilation, and air conditioning (HVAC) systems: A case study in smart buildings by Vinoth Kanna I, Raja Subramani, Maher Ali Rusho, Shubham Sharma, Ramachandran T, Abinash Mahapatro, Deepak Gupta, Jasmina Lozanovic

“…The results illustrate the outstanding performance of hybrid swarm intelligence algorithms to improve HVAC efficiency and occupant comfort, a scalable and inexpensive solution for smart building management. …”
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Optimizing travel time reliability with XAI: A Virginia interstate network case using machine learning and meta-heuristics by Navid Khorshidi, Shahriar Afandizadeh Zargari, Soheil Rezashoar, Hamid Mirzahossein

“…This paper applies machine learning models to predict travel time reliability in transportation networks, using XGBoost, LightGBM, and CatBoost optimized with seven metaheuristic algorithms. …”
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A Comparative Analysis of Hyper-Parameter Optimization Methods for Predicting Heart Failure Outcomes by Qisthi Alhazmi Hidayaturrohman, Eisuke Hanada

“…The XGBoost models exhibited moderate improvement (+0.01683) post-validation. …”
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Dual-Modal Approach for Ship Detection: Fusing Synthetic Aperture Radar and Optical Satellite Imagery by Mahmoud Ahmed, Naser El-Sheimy, Henry Leung

“…This framework incorporates a detection system for optical images that utilizes Contrast Limited Adaptive Histogram Equalization (CLAHE) in combination with the YOLOv7 model to improve accuracy and processing speed. For SAR images, a customized Detection Transformer model, SAR-EDT, integrates advanced denoising algorithms and optimized pooling configurations. …”
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Handwriting Difficulties: A Review of Recent Advances in the Identification and Intervention by Suatmi Murnani, Kazuharu Hashitsume, Tomohiko Igasaki

“…Key techniques examined include the use of spatiotemporal signals, image data, feature-extraction methods, and algorithmic classification. We also explored key experimental design elements and assistive interventions aimed at improving handwriting performance. …”
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An efficient cost calculation method for disparity estimation of stereo matching considering shadow occlusion by Hongjun Sha, Wei Yuan, Xunping Wang, Xiuliu Yuan, Shunichi Koshimura

“…The qualitative and quantitative evaluation results show that MCSP is superior to two classical cost calculation methods and shows good transferability and applicability in the popular disparity estimation algorithms, which can significantly enhance the definition of the edges of the ground objects and improve the quality of the disparity estimation in the shadow occlusion areas.…”
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Deep learning (DL)‐based advancements in prostate cancer imaging: Artificial intelligence (AI)‐based segmentation of 68Ga‐PSMSA PET for tumor volume assessment by Sharjeel Usmani, Khulood Al Riyami, Subash Kheruka, Shah P Numani, Rashid al Sukaiti, Maria Ahmed, Nadeem Pervez

“…Artificial intelligence (AI)‐based segmentation techniques offer a promising solution to these challenges. AI algorithms, such as deep learning‐based models, have shown remarkable performance in automating tumor segmentation tasks with high accuracy and efficiency. …”
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Machine Learning Approaches to Predict Patient’s Length of Stay in Emergency Department by Mohammad A. Shbool, Omar S. Arabeyyat, Ammar Al-Bazi, Abeer Al-Hyari, Arwa Salem, Thana’ Abu-Hmaid, Malak Ali

“…The proposed model is compared with other ML approaches to justify its superiority. …”
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Leveraging Multilingual Transformer for Multiclass Sentiment Analysis in Code-Mixed Data of Low-Resource Languages by Muhammad Kashif Nazir, Cm Nadeem Faisal, Muhammad Asif Habib, Haseeb Ahmad

“…Additionally, the proposed model outperformed other transformer-based models, as well as deep learning and machine learning algorithms in sentiment extraction from code-mixed data. …”
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Geotri-VIO: geometrically consistent multi-prism projection for panoramic imaging in visual-inertial-odometry by Ruidong Mei, Yihan Tu, Lanxiang Zheng, MingXin Wei, Hui Cheng

“…However, the nonlinear distortions caused by the lack of geometric consistency in projection models for panoramic images pose significant challenges to feature extraction and tracking algorithms. …”
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MCAF-Net: Multi-Channel Temporal Cross-Attention Network with Dynamic Gating for Sleep Stage Classification by Xuegang Xu, Quan Wang, Changyuan Wang, Yaxin Zhang

“…Automated sleep stage classification is essential for objective sleep evaluation and clinical diagnosis. While numerous algorithms have been developed, the predominant existing methods utilize single-channel electroencephalogram (EEG) signals, neglecting the complementary physiological information available from other channels. …”
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Deep learning object detection-based early detection of lung cancer by Kuo-Yang Huang, Kuo-Yang Huang, Kuo-Yang Huang, Che-Liang Chung, Che-Liang Chung, Che-Liang Chung, Jia-Lang Xu

“…The Lung-PET-CT-Dx public dataset was used for the model training and evaluation. The performance of the You Only Look Once (YOLO) series of models in the lung CT image object detection task is compared in terms of algorithms, and different versions of YOLOv5, YOLOv8, YOLOv9, YOLOv10, and YOLOv11 are examined for lung cancer detection and classification. …”
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A panting behavior-driven assessment framework for summer ventilation quality optimization in layer houses by Zixuan Zhou, Lihua Li, Hao Xue, Yuchen Jia, Yao Yu, Zongkui Xie, Yuhan Gu

“…The YOLOv10-BCE panting behavior detection model was developed by embedding the BiFormer module into the backbone network to enhance multi-dimensional feature extraction, compressing neck structure parameters using the C3Ghost module, and integrating Efficient Intersection over Union (EIOU) loss to improve detection accuracy and convergence speed. …”
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MHFS-FORMER: Multiple-Scale Hybrid Features Transformer for Lane Detection by Dongqi Yan, Tao Zhang

“…Furthermore, a significant drawback of most existing lane-detection algorithms lies in their reliance on complex post-processing and strong prior knowledge. …”
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Using video for reconstruction in SfM. The Capo d’Omo Tower on Mount Argentario by Fabio Lanfranchi, Piero Barlozzini, Luca Martelli

“…Even more widespread are so-called unmanned aircraft systems (UAS), inoffensive and lighter than 250 g, due to the simplification of the related standards and continued improvements in their acquisition devices. The most advanced photo-modelling programs are now able to process video clips directly, automatically selecting the photos suitable for input in scale-invariant feature transform (SIFT) and speeded up robust features (SURF) algorithms, essential aspects of structure from motion (SfM). …”
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Hybrid Electric Propulsion Design and Analysis Based on Regional Aircraft Mission by Wenjuan Shan, Shengze Bao, Shixuan Lin, Le Kang

“…This study develops an integrated design methodology for hybrid propulsion systems for aircraft, incorporating multidisciplinary algorithms to establish an overall performance model. …”
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Identification method for wheel/rail tread defects based on integrated partial convolutional network by CHENG Xiang, HE Jing, ZHANG Changfan, JIA Lin

“…Additionally, the design incorporated a novel loss function to improve the integration of the proposed strategies and enhance the model's focus on the samples, with its principles clearly explained. …”
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An AI framework for counterattack detection and decision-making evaluation in football by Jiangyan Yang, Huanmin Ge, Yixiong Cui

“…A dataset of 101,710 frames was selected based on specific algorithmic rules from synchronized StatsBomb event data and tracking data of 580 Premier League matches. …”
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Detection of Right and Left Ventricular Dysfunction in Pediatric Patients Using Artificial Intelligence–Enabled ECGs by Scott Anjewierden, Donnchadh O'Sullivan, Kathryn E. Mangold, Grace Greason, Itzhak Zachi Attia, Francisco Lopez‐Jimenez, Paul A. Friedman, Samuel J. Asirvatham, Jason Anderson, Benjamin W. Eidem, Jonathan N. Johnson, Shisheer Havangi Prakash, Talha Niaz, Malini Madhavan

“…Conclusions An artificial intelligence–enabled ECG demonstrates accurate detection of both LVSD and RVSD in pediatric patients. While adult‐trained models offer good performance, improvements are seen when training pediatric‐specific models.…”
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