The evaluation of the efficiency of Atellica UAS800 in detecting pathogens (rod, cocci) causing urinary tract infection by Topcuoglu Canan, Guler Ezgi, Ozyurt Esra, Dinc Bedia, Akbiyik Filiz, Sezer Sevilay, Yilmaz Fatma Meric, Erel Ozcan

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Bridging the Gap Between Computational Efficiency and Segmentation Fidelity in Object-Based Image Analysis by Fernanda Pereira Leite Aguiar, Irenilza de Alencar Nääs, Marcelo Tsuguio Okano

“…A critical issue in image analysis for analyzing animal behavior is accurate object detection and tracking in dynamic and complex environments. …”
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Epidemic features and megagenomic analysis of childhood Mycoplasma pneumoniae post COVID-19 pandemic: a 6-year study in southern China by Yi Xu, Chen Yang, Panpan Sun, Fansen Zeng, Qian Wang, Jianlong Wu, Chunxiao Fang, Che Zhang, Jinping Wang, Yiling Gu, Xiaohuan Wu, Xiaoxian Zhang, Bin Yang, Juhua Yang, Hongwei Zhang, Jiacee Lian, Jinqiu Zhang, Li Huang, Qizhou Lian

“…With the atypical rise of Mycoplasma pneumoniae infection (MPI) in 2023, prompt studies are needed to determine the current epidemic features and risk factors with emerging trends of MPI to furnish a framework for subsequent investigations. …”
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Integrative analysis of gene expression and DNA methylation through one‐class logistic regression machine learning identifies stemness features in medulloblastoma by Hao Lian, Yi‐Peng Han, Yu‐Chao Zhang, Yang Zhao, Shan Yan, Qi‐Feng Li, Bao‐Cheng Wang, Jia‐Jia Wang, Wei Meng, Jian Yang, Qin‐Hua Wang, Wei‐Wei Mao, Jie Ma

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Artificial intelligence networks for assessing the prognosis of gastrointestinal cancer to immunotherapy based on genetic mutation features: a systematic review and meta-analysis by Narges Norouzkhani, Hesam Mobaraki, Shirin Varmazyar, Hadis Zaboli, Zhina Mohamadi, Golnaz Nikeghbali, Kamyar Bagheri, Newsha Marivany, Mirmehdi Najafi, Mahdiyeh Nozad Varjovi, Mohamed Abouzeid, Hanieh Zeidi Baghrabad, Pooya Eini, Aida Azhdarimoghaddam, Farbod Khosravi, Mahsa Asadi Anar

“…Heterogeneity was low to moderate, and no publication bias was detected. Subgroup analysis showed higher AUC for gastric cancer models (AUC: 0.87) and lower for pancreatic cancer models (AUC: 0.52). …”
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Multilevel and multidimensional features of socioeconomic status and cognitive function in older adulthood: a cross-sectional analysis of the IGNITE studyResearch in context by Jermon A. Drake, Lu Wan, Chaeryon Kang, Peter J. Gianaros, Patricio Solis-Urra, Haiqing Huang, Rebecca Reed, Charles H. Hillman, Eric D. Vidoni, Jeffrey M. Burns, Arthur F. Kramer, Edward McAuley, George Grove, Kirk I. Erickson, Lauren E. Oberlin

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Lab-to-Field Generalization Gap: Assessment of Transfer Learning for Bearing Fault Detection by Eleonora Iunusova, Andreas Archenti

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A Wide and Weighted Deep Ensemble Model for Behavioral Drifting Ransomware Attacks by Umara Urooj, Bander Ali Saleh Al-rimy, Mazen Gazzan, Anazida Zainal, Eslam Amer, Mohammed Almutairi, Stavros Shiaeles, Frederick Sheldon

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Classification of Skin Lesion With Features Extraction Using Quantum Chebyshev Polynomials and Autoencoder From Wavelet-Transformed Images by Farhatullah, Xin Chen, Deze Zeng, Jiafeng Xu, Rab Nawaz, Rahmat Ullah

“…Two distinct feature extractors are used to extract key features: Quantum Chebyshev polynomials for initial feature extraction, followed by an Autoencoder (AE) for feature refinement and dimensionality reduction. …”
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Analysis of vehicle and pedestrian detection effects of improved YOLOv8 model in drone-assisted urban traffic monitoring system. by Huili Dou, Sirui Chen, Fangyuan Xu, Yuanyuan Liu, Hongyang Zhao

“…The multi-scale feature fusion module enhances the model's detection ability for targets of different sizes by combining feature maps of different scales; the improved non-maximum suppression algorithm effectively reduces repeated detection and missed detection by optimizing the screening process of candidate boxes. …”
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Early detection of gray mold on eggplant leaves using hyperspectral imaging technique by FENG Lei, ZHANG De-rong, CHEN Shuang-shuang, FENG Bin, XIE Chuan-qi, CHEN Youyuan, HE Yong

“…The pictures on three feature wavelengths were selected by principal component analysis (PCA), which was a good method to reduce the dimension of hyperspectral data. …”
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Design and Analysis of Sowing Depth Detection and Control Device for Multi-Row Wheat Seeders Adapted to Different Terrain Variations by Yueyue Li, Bing Qi, Encai Bao, Zhong Tang, Yi Lian, Meiyan Sun

“…PCA analysis is conducted to correlate terrain feature values with sowing depth deviations. …”
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Robust Multi-Input Multi-Output Analysis for Crop Row Segmentation and Furrow Line Detection in Diverse Agricultural Fields by Muhammad Ibrahim Zain Ul Abideen, Dewa Made Sri Arsa, Talha Ilyas, Hyunggi Jo, Sang Cheol Kim, Hyongsuk Kim

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Leveraging hybrid model of ConvNextBase and LightGBM for early ASD detection via eye-gaze analysis by Ranjeet Bidwe, Sashikala Mishra, Simi Bajaj, Ketan Kotecha

“…This research introduces a novel method for eye gaze analysis to identify autistic traits in children. This proposed work offers • A novel method of ConvNextBase and LightGBM leveraging eye position as a feature for early detection of autistic traits. • A new ConvNextBase architecture proposed with few unfreezed layers and extra dense layers with units of 512 and 128, respectively, and dropout layers with a rate of 0.5 that extract rich, high-level, and more complex features from the images to improve generalization and mitigate overfitting. • A LightGBM model performed classification using 3-fold cross-validation and found the best parameters for bagging_function, feature_fraction, max_depth, Number_of_leaves and learning_rate with values of 0.8, 0.8, −1, 31 and 0.1 respectively, to improve the model's robustness on unseen data.This proposed method is trained and tested on the publicly available Kaggle dataset, and results are benchmarked with other state-of-the-art methods. …”
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Efficient Deep Learning-Based Cyber-Attack Detection for Internet of Medical Things Devices by Abigail Judith, G. Jaspher W. Kathrine, Salaja Silas, Andrew J

“…The study utilizes principal component analysis (PCA) for feature reduction and employs multi-layer perceptron to classify unforeseen cyber-attack IoT-based healthcare devices. …”
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Integrated Machine Learning and Region Growing Algorithms for Enhanced Concrete Crack Detection: A Novel Approach by Wenxuan Yao, Hui Li, Yanlin Li

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Optimizing Stroke Recognition With MediaPipe and Machine Learning: An Explainable AI Approach for Facial Landmark Analysis by Reshad Ul Karim, Sammam Mahdi, Abrar Samin, Aniqua Nusrat Zereen, M. Abdullah-Al-Wadud, Jia Uddin

“…This study presents an innovative approach to stroke diagnosis through the analysis of facial landmarks combining MediaPipe’s facial landmark detection with advanced machine learning models’ Random Forest (RF), Extreme Gradient Boosting (XGB), and Categorical Boosting (CB). …”
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Validation of a deep learning model for cattle lameness detection: Comparison of human scorer performance and automated gait analysis by Sandra Reitmaier, Serhan Narli

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Automatic Detection of Concrete Spalling Using Piecewise Linear Stochastic Gradient Descent Logistic Regression and Image Texture Analysis by Nhat-Duc Hoang, Quoc-Lam Nguyen, Xuan-Linh Tran

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Morphological Analysis and Subtype Detection of Acute Myeloid Leukemia in High-Resolution Blood Smears Using ConvNeXT by Mubarak Taiwo Mustapha, Dilber Uzun Ozsahin

“…A deep learning pipeline was developed, integrating Stochastic Weight Averaging (SWA) for model stability, Mixup data augmentation to enhance generalization, and Grad-CAM for model interpretability, ensuring biologically meaningful feature visualization. Various models, including ResNet50 and Vision Transformers, were benchmarked for comparative performance analysis; (3) Results: ConvNeXt outperformed ResNet50, achieving a classification accuracy of 95% compared to 91% for ResNet50 and 81% for transformer-based models (Vision Transformers). …”
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