MRI Features and Neutrophil-to-Lymphocyte Ratio (NLR)-Based Nomogram to Predict Prognosis of Microvascular Invasion-Negative Hepatocellular Carcinoma by Wei Y, Huang X, Pei W, Zhao Y, Liao H

“…We created a predictive model that relies on MRI features (tumor size and tumor capsule) and neutrophil-to-lymphocyte ratio (NLR). …”
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Pixel-Based Change Detection in Moving-Camera Videos Using Twin Convolutional Features on a Data-Constrained Scenario by Luiz G. C. Tavares, Allan F. Da Silva, Rafael Padilla, Lucas A. Thomaz, Sergio L. Netto, Eduardo A. B. Da Silva

“…In addition, in order to deal with the challenges of training with high-dimensional data, a complexity-reducing training strategy that eliminates the need for large training sets while maintaining a robust detection performance was proposed. The PBCD-MC is assessed using a newly developed pixel-level annotated dataset (VDAO-AS) and is shown to outperform state-of-the-art models, achieving overall <inline-formula> <tex-math notation="LaTeX">$MCC=0.877$ </tex-math></inline-formula> and overall <inline-formula> <tex-math notation="LaTeX">$DIS=0.092$ </tex-math></inline-formula> on a pixel-level detection, results that are significantly better than those of its competitors. …”
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Design and Performance Verification of Bionic Octopus Sucker Sealing Structure for Solenoid Valves by Zhihong Wang, Xinbin Zhang, Zhengzhi Mu, Xiang Guan, Junchi Liu, Zhipeng Pan, Junchong Wang, Xiangrui Ye, Zhenghai Qi, Jianyang Dong, Yongming Yao, Liucheng Zhou

“…By extracting the microscopic groove morphology features of the octopus sucker, we designed a multilayer rectangular cross-section groove structure at the annular interface, combined the designed structure with the Abaqus cohesive model to simulate the interface stripping behavior, and verified its mechanical properties by the pull-out test. …”
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Immunohistochemical Features of MMP-9 and pSTAT1 in Granuloma Annulare and Sarcoidosis: A Comparative Study of 62 Cases by Ze Wu, Linghui Li, Hui Qu, Rui-Qun Qi, Jun Niu

“…To identify the histological and immunohistochemical (IHC) features of GA and sarcoidosis. Methods. A retrospective review of 36 patients with GA and 26 with sarcoidosis was performed. …”
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Two-Dimensional Lattice Complexity Features of Abdominal CT Images to Predict Patient Survival After Hepatectomy for Hepatocellular Carcinoma by Yu Wang, Xiaoqiong Jiang, Shi Xu, Daguan Ke, Ruixia Wu

“…These features were assessed for performance of support vector machine predictive models through the receiver operator characteristic curve and area under the curve. …”
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Intrusion detection system based on machine learning using least square support vector machine by Pratik Waghmode, Manideep Kanumuri, Hosam El-Ocla, Tanner Boyle

“…Consequently, the accuracy of an ML model likely declines when irrelevant features are included from a vast dataset. …”
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Radiomic features of PET/CT imaging of large B cell lymphoma lesions predicts CAR T cell therapy efficacy by Yoganand Balagurunathan, Zhouping Wei, Jin Qi, Zachary Thompson, Erin Dean, Erin Dean, Hong Lu, Hong Lu, Saran Vardhanabhuti, Salvatore Corallo, Jung W. Choi, Jenny J. Kim, Mike Mattie, Michael Jain, Frederick L. Locke

“…Principal component (PC) analysis was performed to reduce the dimensionality in feature-based functional categories: size (n=38), shape (n=9), and texture (n=259). …”
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Machine Learning-Based Seismic Response Prediction for Nuclear Power Plant Structures Considering Aging Deterioration by Hyunsu Kim, Soyeon Lee, Junsu Jang, Sihyeon An

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BLSF: Adaptive Learning for Small-Sample Medical Data With Broad Learning System Forest Integration by Dimas Chaerul Ekty Saputra, Khamron Sunat, Tri Ratnaningsih

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High-fidelity EEG feature-engineered taxonomy for bruxism and PLMS prognostication through pioneering and avant-garde ML frameworks by Shivam Tiwari, Deepak Arora, Barkha Bhardwaj

“…The results show how well machine learning methods and EEG feature extraction might diagnose sleep problems. …”
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Automatic identification of music performer using the linear prediction cepstral coefficients method by Magdalena CHUDY

“…The performers' models based on the LPCC features and vector quantization are proposed as methods of classification. …”
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Adaptive Graph Convolutional Network with Deep Sequence and Feature Correlation Learning for Porosity Prediction from Well-Logging Data by Long Hao, Xun Wang, Yunlong Dong, Peizhi Zhao, Peifu Han, Xue Li, Fengrui Jing, Chuchu Zhai

“…We demonstrated our method on well-logging datasets and comprehensively compared its performance with other deep learning models, showing its superiority in predicting porosity from well-logging data. …”
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Historical Manuscripts Analysis: A Deep Learning System for Writer Identification Using Intelligent Feature Selection with Vision Transformers by Merouane Boudraa, Akram Bennour, Mouaaz Nahas, Rashiq Rafiq Marie, Mohammed Al-Sarem

“…Leveraging vision transformer models, our methodology effectively learns complex patterns and features from extracted patches, enabling precise identification of writers across historical manuscripts. …”
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Machine Learning-Based Ensemble Feature Selection and Nested Cross-Validation for miRNA Biomarker Discovery in Usher Syndrome by Rama Krishna Thelagathoti, Dinesh S. Chandel, Wesley A. Tom, Chao Jiang, Gary Krzyzanowski, Appolinaire Olou, M. Rohan Fernando

“…Machine learning models were trained and tested using this subset, followed by validation on an independent 10% sample. …”
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A Comprehensive Approach to Intrusion Detection in IoT Environments Using Hybrid Feature Selection and Multi-Stage Classification Techniques by G. Logeswari, J. Deepika Roselind, K. Tamilarasi, V. Nivethitha

“…Specifically, it achieves 98.83% accuracy, 98.56% precision, and 98.65% F-Measure on the TON-IoT dataset, and 98.6% accuracy, 98.5% precision, and 98.94% F-Measure on the BOT-IoT dataset, showcasing its superior performance over existing IDS models. This paper&#x2019;s key contribution lies in the integration of feature selection and classification techniques tailored for IoT environments, filling a critical gap in the state of the art and offering a more adaptive and efficient solution for real-time intrusion detection.…”
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A novel hybrid approach for thyroid disease detection: Integrating cuttlefish algorithm and simulated annealing for optimal feature selection by Kapil Shrivastava, Saroj Pandey, Rishav Dubey, Mayank Namdev, Vipin Tiwari, Aditi Sharma

“…The proposed hybrid algorithm method finds the best features for finding thyroid disease uses performance measures such as accuracy, F1-score, precision, and recall. …”
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Harnessing machine learning for high-throughput screening of high thermal conductivity polyimides: A multiscale feature engineering approach by Jiale Han, Chunhua Ying, Yue Cao, Wen Li, Yuan Feng, Masood Mortazavi, Pingfan Wu, Liang Peng, Jiechen Wang

“…This process results in the creation of a comprehensive combinational feature set. Multiple machine learning models were trained and validated, demonstrating high predictive accuracy and generalizability. …”
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Fusion of transfer learning with nature-inspired dandelion algorithm for autism spectrum disorder detection and classification using facial features by G. Elangovan, N. Jagadish Kumar, J. Shobana, M. Ramprasath, Gyanendra Prasad Joshi, Woong Cho

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DMF-YOLO: Dynamic Multi-Scale Feature Fusion Network-Driven Small Target Detection in UAV Aerial Images by Xiaojia Yan, Shiyan Sun, Huimin Zhu, Qingping Hu, Wenjian Ying, Yinglei Li

“…However, traditional detection models suffer significant performance degradation due to challenges including substantial scale variations, high proportions of small targets, and dense occlusions in UAV-captured images. …”
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Evolution of the Limpopo River Basin in Botswana based on morphometric and morphotectonic features from selected rivers using GIS techniques by One Moses, Read B Mapeo, Joyce G Maphanyane

“…Drainage network extraction was performed using the Arc Hydro extension in ArcGIS 10.5. …”
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