Monitoring Critical Mountain Vertical Zonation in the Surkhan River Basin Based on a Comparative Analysis of Multi-Source Remote Sensing Features by Wenhao Liu, Hong Wan, Peng Guo, Xinyuan Wang

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Enhanced MRI brain tumor detection using deep learning in conjunction with explainable AI SHAP based diverse and multi feature analysis by Asif Rahman, Maqsood Hayat, Nadeem Iqbal, Fawaz Khaled Alarfaj, Salem Alkhalaf, Fahad Alturise

“…This study investigates the synergy among multiple feature representation schemes such as local Binary Patterns (LBP), Gabor filters, Discrete Wavelet Transform, Fast Fourier Transform, Convolutional Neural Networks (CNN), and Gray-Level Run Length Matrix alongside five learning algorithms namely: k-nearest Neighbor, Random Forest, Support Vector Classifier (SVC), and probabilistic neural network (PNN), and CNN. …”
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Study and restoration of the costume of the HuoLang (Peddler) in the Ming Dynasty of China by Zhu Chun, Gao Yuanyuan, Wang Jianping, Zeng Xianyi, Bruniaux Pascal, Liu Kaixuan

“…This study looks at two aspects of ancient Chinese genre painting to interpret the more realistic ancient shopping scenes in the painting of the peddler in spring scenery in the Ming Dynasty, namely, the Ming spring scene and the characters’ costume image features. Through the analysis of the detailed characteristics of the style, structure, pattern, and color of the figure costume in the painting of the peddler, a total of five sets of figure costume for an adult male and four children in the painting of the peddler in the spring scenery of the Ming Dynasty in China were digitally restored using the 3D virtual fitting technology, which clearly showed the characteristics of the figure costume of the peddler and children in the Ming Dynasty (1368–1644). …”
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Fine identification of vegetation types in open pit mining regions using combined UAV RGB imagery and LiDAR point cloud data by Suling He, Yuncheng Deng, Jinliang Wang, Mengjia Luo

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Genome-wide identification and expression analysis of the ADH gene family in Artemisia annua L. under UV-B stress by Hengyu Pan, Peiqi Shi, Shan Zhong, Xiaoxia Ding, Shengye Bao, Siyu Zhao, Jieting Chen, Chunyan Dai, Danchun Zhang, Xiaohui Qiu, Baosheng Liao, Zhihai Huang

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Computer Tomography Features of Antineutrophil Cytoplasm Antibody-associated Vasculitis-interstitial Lung Disease and Its Correlation with Antineutrophil Cytoplasmic Antibody Conce... by Hongmei WANG, Junlin LI, Yuqing DONG, Yueyang ZHANG, Renhuan YAO

“…CT imaging data were analyzed qualitatively and quantitatively to evaluate lesion types (e.g., ground-glass opacities, reticulations, honeycombing, consolidation, and traction bronchiectasis) and their distribution patterns. The severity of the lesions was quantified using a pulmonary fibrosis scoring system, and the correlation between imaging features and laboratory indices was analyzed. …”
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An enhanced machine learning approach with stacking ensemble learner for accurate liver cancer diagnosis using feature selection and gene expression data by Amena Mahmoud, Eiko Takaoka

“…We employed a feature selection process to identify the most relevant gene expressions associated with liver cancer. …”
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Computational image and molecular analysis reveal unique prognostic features of immune architecture in African Versus European American women with endometrial cancer by Sepideh Azarianpour, Sirvan Khalighi, Arpit Aggarwal, Vidya Sankar Viswanathan, Pingfu Fu, Stefanie Avril, Anant Madabhushi

“…We identified the differences in immune cell spatial patterns between AA and EA populations with markers of tumor biology, including histologic and molecular subtypes. …”
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Leverage Gaussian Interpolation Features Extraction and Advanced Encode–Decode Models for 2D Steady State Flows Estimation by Thi-Thu-Huong Le, Changwoo Choi, Junyoung Son, Howon Kim

“…This paper introduces a novel approach that combines Gaussian interpolation-based feature extraction with advanced encode-decode models, including AutoEncoder, UNet, and DeepLabV3+. …”
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Using Hybrid Feature and Classifier Fusion for an Asynchronous Brain–Computer Interface Framework Based on Steady-State Motion Visual Evoked Potentials by Bo Hu, Jun Xie, Huanqing Zhang, Junjie Liu, Hu Wang

“…The method integrates filter bank common spatial patterns (FBCSPs) and filter bank canonical correlation analysis (FBCCA) to extract complementary spatial and frequency domain features from EEG signals. …”
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FEATURES OF EVALUATING THE RATIONALITY OF CONSUMER BEHAVIOR AT ALL STAGES OF USING NON-STEROIDAL ANTI-INFLAMMATORY DRUGS IN OCCUPATIONAL DISEASES OF THE MUSCULOSKELETAL SYSTEM by Андрей Георгиевич Петров, Сергей Николаевич Филимонов, Виктор Андреевич Семенихин, Ольга Владимировна Хорошилова

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Passive Radar Low Slow Small Detection Dataset (LSS-PR-1.0) and Multi-domain Feature Extraction and Analysis Methods by Xiaolong CHEN, Guilin RAO, Jian GUAN, Jinhao WANG, Hongyong WANG, Caisheng ZHANG, Jianxin YI, Xianrong WAN, Yunhua RAO

“…On this basis, four categories of ten multi-domain feature extraction and analysis methods are proposed, including time-domain features (relative average amplitude), frequency-domain features (spectral features, Doppler waterfall plot, and range Doppler features), time-frequency-domain features, and motion features (heading difference, trajectory parameters, speed variation interval, speed variation coefficient, and acceleration). …”
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Association between dermoscopic features and tumor thickness, diameter, age, and sex in acral melanoma: A cross-sectional studyCapsule Summary by Yaei Togawa, MD, PhD, Yosuke Yamamoto, MD, PhD, Keisuke Suehiro, MD, Yuki Shiko, PhD, Kohei Takahashi, MS, Yohei Kawasaki, PhD, Hiroyuki Matsue, MD, PhD, Takashi Inozume, MD, PhD

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A novel double machine learning approach for detecting early breast cancer using advanced feature selection and dimensionality reduction techniques by Suganya Athisayamani, Tamilazhagan S, A. Robert Singh, Jae-Yong Hwang, Gyanendra Prasad Joshi

“…This approach effectively captures both structured features and non-linear patterns, making it suitable for datasets with complex dependencies. …”
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Pericoronary adipose tissue radiomics features as imaging markers for coronary artery disease risk assessment: insights from gene expression analysis by Yan Li, Weimin Zhang, Yahui Hu, Zheng Xu, Qiang Huo, Haicheng Qi, Qian Liu, Yan Xing

“…Conclusions Our findings demonstrated a significant correlation between PCAT radiomics features and gene expression patterns in CAD patients. …”
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Enhanced Tolerance to Antifungals as a General Feature of Rho⁻ Mutants in Yeast Species: Implications to Positive Selection of Respiratory Deficiency by Zachary Johnson, Farhan Nadim, Mikhajlo K. Zubko

“…We observed partial (not complete) inhibition in WT, with four different types of ZOI patterns that were species- and antifungal-specific. …”
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Retrieval of Soil Moisture in the Yutian Oasis, Northwest China by 3D Feature Space Based on Optical and Radar Remote Sensing Data by Yilizhati Aili, Ilyas Nurmemet, Shiqin Li, Xiaobo Lv, Xinru Yu, Aihepa Aihaiti, Yu Qin

“…Through systematic analysis of feature space partitioning patterns across soil moisture gradients, the Optical–Radar Soil Moisture Retrieval Index (ORSMRI) was proposed, and fitting analysis was conducted by measured soil moisture. …”
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Rethinking Radiation Therapy for Perineural Invasion in Oral Cancer: Does More Coverage Improve Outcomes? by Sarbani Ghosh Laskar, Anuj Kumar, Ashwini Adhau, Shwetabh Sinha, Samarpita Mohanty, Munita Bal, Neha Mittal, Swapnil Rane, Asawari Patil, Ashwini Budrukkar, Monali Swain, Pallavi Rane, Gouri Pantvaidya, Sudhir Nair, Deepa Nair, Anuja Deshmukh, Shivakumar Thiagarajan, Richa Vaish, Vidisha Tuljapurkar, Chandrashekhar Dravid, Poonam Joshi, Rathan Shetty, Arjun Singh, Pankaj Chaturvedi

“…All patients underwent surgery followed by adjuvant RT, with or without concurrent chemotherapy. Recurrence patterns were categorised as in‐field, marginal or out‐of‐field. …”
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Detecting Malware C&C Communication Traffic Using Artificial Intelligence Techniques by Mohamed Ali Kazi

“…These feature selection algorithms are also compared with a manual feature selection approach to determine whether a manual, automated, or hybrid feature selection approach would be more suitable for this type of problem.…”
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Use of Socio-economic, Climatic, and Land use Land Cover Patterns in Solid Waste Forecasting with Integrated Gradient LSTNet Based Model in Lomé, Togo by Kanlanféi Sambiani, Yendoubé Lare, Adamou Zanguina, Satyanarayana Narra

“…This study aimed to develop a new approach of Integrated Gradient Long- and Short-term Time series Network (LSTNet+IG)-based models, assess the baseline neural network models, and provide features influences explanation on MSW generation by using socio-economic, climatic, and Land Use Land Cover (LULC) patterns. …”
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