Diagnostic performance and clinical utility of metagenomic next-generation sequencing in suspected central nervous system infections: a prospective comparative study by Xiao-guang Cao, Xiong-feng Zhu, Zha Yu, Chun-yan Wang, Min Shao, Hua-dong Meng, Chong-jian Huang

“…Receiver operating characteristic (ROC) analysis demonstrated superior diagnostic accuracy for continuous CSF variables over binary ones, with mNGS showing robust performance [area under the curve (AUC) = 0.794].ConclusionmNGS offers rapid and accurate pathogen detection, outperforming conventional methods in sensitivity and turnaround time, and provides valuable guidance for individualized antimicrobial treatment in CNS infections.…”
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Enhanced Detection of Intrusion Detection System in Cloud Networks Using Time-Aware and Deep Learning Techniques by Nima Terawi, Huthaifa I. Ashqar, Omar Darwish, Anas Alsobeh, Plamen Zahariev, Yahya Tashtoush

“…This study introduces an enhanced Intrusion Detection System (IDS) framework for Denial-of-Service (DoS) attacks, utilizing network traffic inter-arrival time (IAT) analysis. …”
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Detection of prospective areas for mineralization deposits using image analysis technique of aeromagnetic data around Marsa Alam-Idfu road, Eastern Desert, Egypt by A.S.M. Assran, R.A.Y. El Qassas, M.H.M. Yousef

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Prediction of Early Diagnosis in Ovarian Cancer Patients Using Machine Learning Approaches with Boruta and Advanced Feature Selection by Tuğçe Öznacar, Tunç Güler

“…This research aims to assess the feature extraction process from various machine learning techniques for better modelling of ovarian cancer and the selection process in ovarian cancer analysis. …”
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Detection of Retinal and Choriocapillaris Microvascular Changes in Retinal Vein Occlusion and Fellow Eyes by Optical Coherence Tomography Angiography: A Systematic Review and Meta-... by Linxin Wei, Qing Zhao, Youxin Chen

“…Abstract Introduction This study aims to summarize the retinal and choroidal microvascular features detected by optical coherence tomography angiography (OCTA) in the affected and fellow eyes of patients with retinal vein occlusion (RVO). …”
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An Accurate LiDAR-Inertial SLAM Based on Multi-Category Feature Extraction and Matching by Nuo Li, Yiqing Yao, Xiaosu Xu, Shuai Zhou, Taihong Yang

“…First, we employ a robust multi-category feature extraction method based on principal component analysis (PCA), which effectively filters out noisy and weakly structured points, ensuring stable feature representation. …”
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Classification of Lung Nodule Using Hybridized Deep Feature Technique by Malin Bruntha, Immanuel Alex Pandian, Siril Sam Abraham

“…The dimensionality reduction technique, Principle Component Analysis (PCA) has been introduced to improve the performance of hybridized features with SVM. …”
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Graphical Empirical Mode Decomposition–Convolutional Neural Network-Based Expert System for Early Corrosion Detection in Truss-Type Bridges by Alan G. Lujan-Olalde, Angel H. Rangel-Rodriguez, Andrea V. Perez-Sanchez, Martin Valtierra-Rodriguez, Jose M. Machorro-Lopez, Juan P. Amezquita-Sanchez

“…This study proposes an expert system based on a novel methodology for corrosion detection using vibration signal analysis. The approach employs graphical empirical mode decomposition (GEMD) to decompose vibration signals into their intrinsic mode functions, extracting relevant structural features. …”
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Software with artificial intelligence-derived algorithms for detecting and analysing lung nodules in CT scans: systematic review and economic evaluation by Julia Geppert, Peter Auguste, Asra Asgharzadeh, Hesam Ghiasvand, Mubarak Patel, Anna Brown, Surangi Jayakody, Emma Helm, Dan Todkill, Jason Madan, Chris Stinton, Daniel Gallacher, Sian Taylor-Phillips, Yen-Fu Chen

“…Objectives For the detection and analysis of lung nodules in symptomatic, incidental, screening or surveillance populations, the following key questions are asked. …”
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Medical Image Fusion Based on Feature Extraction and Sparse Representation by Yin Fei, Gao Wei, Song Zongxi

“…SM contains the local structure feature captured by the Laplacian of a Gaussian (LOG) and EM contains the energy and energy distribution feature detected by the mean square deviation. …”
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Feature Set to sEMG Classification Obtained With Fisher Score by Diana C. Toledo-Perez, Marcos Aviles, Roberto A. Gomez-Loenzo, Juvenal Rodriguez-Resendiz

“…The central purpose of this research is to develop and validate a methodology that uses the Fisher Score to select a set of features in the classification of sEMG signals. This selected set is descriptive enough to achieve high levels of accuracy in detecting EMG signal patterns across multiple subjects. …”
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Pathological and clinical insights into DICER1 hotspot mutated Sertoli-Leydig cell tumors: a comparative analysis by Zhuoyao Lyu, Yilin Liu, Jingci Chen, Pengyan Wang, Zhaohui Lu, Xiaoyan Chang, Xianlong Chen, Heng Ma, Shengwei Mo, Shuangni Yu, Jie Chen

“…Methods A retrospective analysis was conducted on 50 SLCTs. DICER1 RNase IIIb hotspot mutations were detected by the Sanger sequence. …”
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Lightweight Fire Detection in Tunnel Environments by Shakhnoza Muksimova, Sabina Umirzakova, Dilnoza Abduxalikovna Babaraximova, Young Im Cho

“…This study proposes a lightweight hybrid deep learning (DL) model that integrates Convolutional Neural Networks (CNNs) for spatial feature extraction and Long Short-Term Memory (LSTM) networks for temporal analysis, offering an efficient and robust solution for real-time tunnel fire detection. …”
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An Interpretability Method for Broken Wire Detection by Hailong Wu, Shaoqing Liu, Zhanghou Xu, Zhenshan Ji, Mengpeng Qian, Xiaolin Yuan, Yong Wang

“…Therefore, it is necessary to perform broken wire detection. Deep learning has powerful feature-learning capabilities and is characterized by high accuracy and efficiency, and the YOLOv8 object detection model has been adopted to detect wire breaks in electromagnetic signal images of wire rope, achieving better results. …”
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Enhancing Online Fraud Detection: Leveraging Machine Learning and Behavioral Indicators for Improved Accuracy and Real-Time Detection by Shaha Prasad, Gavekar Vidya

“…A comparative analysis of traditional and advanced ML models, including Logistic Regression, Decision Tree, Random Forest, Support Vector Machine (SVM), Artificial Neural Networks (ANN), and LightGBM, was conducted using real-world fraud detection datasets. …”
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Intelligent Recognition Method for Ferrography Wear Debris Images Using Improved Mask R-CNN Methods by Xiangwen Xiao, Weixuan Zhang, Qing Wang, Yuan Liu, Yishou Wang

“…The improvement on the Mask R-CNN focuses on two key aspects: enhancing feature extraction through the feature pyramid network structure and integrating attention mechanisms. …”
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An innovative deep learning framework for skin cancer detection employing ConvNeXtV2 and focal self-attention mechanisms by Burhanettin Ozdemir, Ishak Pacal

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Unique pathological features and drug resistance patterns in cutaneous tuberculosis by Yuejiao Liu, Runrui Wu, Junjun Liu, Jinlong Dai, Dongxu Liu, Yadong Liu, Yumei Liang, Wen Chen

“…In this study, we conducted a comparative analysis of 59 CTB samples and 59 pulmonary tuberculosis samples, focusing on their clinicopathological features. …”
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Epidemiological and clinical features of lymphoproliferative diseases in the head and neck region by F. Sh. Kamolova, A. M. Mudunov, P. A. Zeynalova, L. Yu. Grivtsova, G. F. Allakhverdieva, R. I. Azizyan, A. A. Akhundov, I. A. Zaderenko, M. V. Bolotin, D. K. Stelmakh, V. I. Sokorutov, K. D. Il’kaev, V. T. Tsiklauri, I. M. Gelfand, M. B. Pak, O. L. Timofeeva, Yu. E. Ryabukhina, F. M. Abbasbeyli, Ts. Chzhao

“…Based on the analysis of clinical and morphological features of head and neck lymphomas, epidemiological and clinical features are described in detail, and differences in the symptoms and clinical manifestations of non-Hodgkin’s and Hodgkin’s lymphomas with a predominant head and neck involvement are revealed.…”
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The effect of strength training with different frequency on untrained university students by Ali E. Cigerci, Harun Genc

“…Background and Study Aim: The target of this paper was to examine the effects of strength training with different frequency on physical, performance and strength features on untrained university male students. …”
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