Machine learning-driven design of wide-angle impedance matching structures for wide-angle scanning arrays by Sina Hasibi Taheri, Javad Mohammadpour, Ali Lalbakhsh, Slawomir Koziel, Stanislaw Szczepanski

“…Decision Tree-based models are chosen to provide accurate prediction while minimizing the dataset preparation time. …”
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Methodology For Extracting Poplar Planted Fields From Very High-Resolution Imagery Using Object-Based Image Analysis and Feature Selection Strategy by E. O. Yilmaz, T. Kavzoglu, I. Colkesen, H. Tonbul, A. Teke

“…The most effective and contributing object features that assure high separability between landscape features were determined using a filter-based Chi-square algorithm for the prediction models constructed with SVM, RF, and RotFor classifiers. …”
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An Optimised CNN Hardware Accelerator Applicable to IoT End Nodes for Disruptive Healthcare by Arfan Ghani, Akinyemi Aina, Chan Hwang See

“…Addressing the challenges posed by constrained dataset sizes, compute-intensive AI algorithms, and hardware limitations, the approach presented in this paper leverages efficient image augmentation and pre-processing techniques to enhance both prediction accuracy and the training efficiency. …”
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Research on RF Intensity Temperature Sensing based on 1D-CNN by DING Meiqi, GUI Lin, WANG Ziyi, SHANG Disen, QIAN Min, LI Qiankun

“…【Results】The experimental results show that the RMSE of the prediction model based on 1D-CNN reaches the order of 10^-3, while the RMSE of the traditional algorithms is usually in the order of 10^-1. …”
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Categorizing Mental Stress: A Consistency-Focused Benchmarking of ML and DL Models for Multi-Label, Multi-Class Classification via Taxonomy-Driven NLP Techniques by Juswin Sajan John, Boppuru Rudra Prathap, Gyanesh Gupta, Jaivanth Melanaturu

“…Building on existing literature, discussions with psychologists and other mental health practitioners, we developed a taxonomy of 27 distinctive markers spread across 4 label categories; aiming to create a preliminary screening tool leveraging textual data.The core objective is to identify the most suitable model for this complex task, encompassing comprehensive evaluation of various machine learning and deep learning algorithms. we experimented with support vector machines (SVM), random forest (RF) and long short-term memory (LSTM) algorithms incorporating various feature combinations involving Term Frequency-Inverse Document Frequency (TF-IDF) and Latent Dirichlet Allocation (LDA). …”
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Single-cell and multi-omics analysis reveals the role of stem cells in prognosis and immunotherapy of lung adenocarcinoma patients by Jianan Zheng, Haoran Lin, Wei Ye, Mingjun Du, Chenjun Huang, Jun Fan

“…Significantly lower immune cell infiltration, characteristic of “cold” tumors, was detected in high-SCPM patients by multiple immune infiltration algorithms. These findings were further validated in the internal cohort, where reduced CD8+ T cell infiltration was observed in high-SCPM patients.ConclusionA stem cell–based prognostic model (SCPM) was constructed and validated, enabling accurate prediction of survival and immunotherapy response in LUAD patients. …”
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Keypoints-Based Multi-Cue Feature Fusion Network (MF-Net) for Action Recognition of ADHD Children in TOVA Assessment by Wanyu Tang, Chao Shi, Yuanyuan Li, Zhonglan Tang, Gang Yang, Jing Zhang, Ling He

“…Existing video-based action recognition algorithms focus on object or interpersonal interactions, they may overlook ADHD-specific behaviors. …”
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A new approach for diabetes risk detection using quadratic interpolation flower pollination neural network by Yulianto Triwahyuadi POLLY, Adriana FANGGIDAE, Juan Rizky Mannuel LEDOH, Clarissa Elfira AMOS PAH, Bertha S. DJAHI, Kisan Emiliano Rape TUPEN

“…These algorithms were tested on a diabetes risk dataset divided into training, validation, and testing subsets. …”
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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

“…Hybrid approaches combining geostatistics with ML algorithms (e.g., RF, Boost, SVM, ANN) demonstrate promise in addressing spatial uncertainty, while RS data enhances covariate enrichment and near-real-time applications. …”
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A rapid, affordable, and reliable method for profiling microbiome biomarkers from fecal images by Donghyeok Lee, Annemiek Maaskant, Huy Ngo, Roy C. Montijn, Jaco Bakker, Jan A.M. Langermans, Evgeni Levin

“…Tailor-made learning algorithms were created by integrating digital images of fecal samples with corresponding whole-genome sequenced microbial profiles. …”
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Real-time locomotion mode detection in individuals with transfemoral amputation and osseointegration by Bahareh Ahkami, Morten B. Kristoffersen, Max Ortiz-Catalan

“…The method was implemented in LocoD, an existing open-source platform, allowing for further development by the community and allowing easy comparison between different classification algorithms. The evaluation of the platform and prediction algorithm relies on quantifying the transition error, signifying instances where the algorithm falls short in predicting shifts between different walking surfaces. …”
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Clinical applications of artificial intelligence and machine learning in neurocardiology: a comprehensive review by Jade Basem, Racheed Mani, Scott Sun, Kevin Gilotra, Neda Dianati-Maleki, Reza Dashti

“…In the focus of cryptogenic strokes, there is promising research elucidating likely underlying cardiac causes and thus, improved treatment options and secondary stroke prevention. While many algorithms still require a larger knowledge base or manual algorithmic training, AI/ML in neurocardiology has the potential to provide more comprehensive healthcare treatment, increase access to equitable healthcare, and improve patient outcomes. …”
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Research on the Evaluation of the Node Cities of China Railway Express Based on Machine Learning by Chenglin Ma, Mengwei Zhou, Wenchao Kang, Haolong Wang, Jiajia Feng

“…The Random Forest model outperformed comparative algorithms with 99.5% prediction accuracy (8.33% higher than conventional classification models), particularly in handling multi-dimensional interactions between urban development factors. …”
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Methodological Integration of Machine Learning and Geospatial Analysis for PM10 Pollution Mapping by Kalid Hassen Yasin, Muaz Ismael Yasin, Anteneh Derribew Iguala, Tadele Bedo Gelete, Erana Kebede

“…The study contributes valuable insights for implementing scalable pollution prediction systems in resource-constrained urban environments while acknowledging interpretability challenges inherent to complex ML models. • Preprocessing of spatial data from various sources, incorporating the handling of missing/abnormal data, analysis, and normalization • Implementation of the three ML algorithms with rigorous hyperparameter tuning, model validation, and performance assessment • Mapping PM10 Hotspots on the Gradient Direction and Distance from the City Center…”
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Visualized hysteroscopic artificial intelligence fertility assessment system for endometrial injury: an image-deep-learning study by Bohan Li, Hui Chen, Hua Duan

“…The study evaluated two image-deep-learning algorithms’ effectiveness in predicting pregnancy within one year, using AUCs and decision curve analysis. …”
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Integrated multiomics analysis and machine learning refine molecular subtypes and prognosis for thyroid cancer by Peng Zhang, Meizhong Qin, Fen Li, Kunpeng Hu, He Huang, Cuicui Li

“…Most existing models rely on single-omics data and limited algorithms, reducing robustness and clinical value. …”
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Transfer Learning-Empowered Physical Layer Security in Aerial Reconfigurable Intelligent Surfaces-Based Mobile Networks by Yosefine Triwidyastuti, Tri Nhu Do, Ridho Hendra Yoga Perdana, Kyusung Shim, Beongku An

“…To address these challenges, we develop robust algorithms for optimizing the phase-shift configurations of RIS. …”
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Machine Learning and Deep Learning Hybrid Approach Based on Muscle Imaging Features for Diagnosis of Esophageal Cancer by Yuan Hong, Hanlin Wang, Qi Zhang, Peng Zhang, Kang Cheng, Guodong Cao, Renquan Zhang, Bo Chen

“…Diagnostic models were developed using deep learning (2D and 3D neural networks) and traditional machine learning (11 algorithms with PyRadiomics-derived features). Multimodal features underwent Principal Component Analysis (PCA) for dimension reduction and were fused for final analysis. …”
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A three-dimensional reconstruction method of coal mine tunnel fused with LiDAR and IMU by Qinghua MAO, Jianquan CHAI, Yanzhang CHEN, Xusheng XUE, Chuanwei WANG

“…Compared with the A-LOAM and LEGO-LOAM algorithms, the proposed algorithm has significantly improved the accuracy and global consistency of pose estimation. …”
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Patterns and risk factors of falls among older adults: a systematic review by Tetiana Yermakova

“…The first algorithm is based on extracting documents with the highest citation metrics. …”
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