Detailed geomorphological cartography of the Fildes Peninsula, South Shetland Islands, Antarctica by P. C. Cazaroto, F. N. J. Villela, C. Miranda, M. R. Francelino, C. E. G. R. Schaefer

“…Using aerial photos (1956), drone images, and previous research, geomorphic features were vectorized. Results indicate predominant processes such as nivation and cryoturbation. …”
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Hyperspectral estimation of chlorophyll content in grapevine based on feature selection and GA-BP by YaFeng Li, XinGang Xu, WenBiao Wu, Yaohui Zhu, LuTao Gao, XiangTai Jiang, Yang Meng, GuiJun Yang, HanYu Xue

“…Comparison of the prediction ability of Random Forest Regression (RFR) algorithm, Support Vector Machine Regression (SVR) model, and Genetic Algorithm-Based Neural Network (GA-BP) on grape LCC based on sensitive features. …”
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Streamlining Thoracic Radiotherapy Quality assurance: One-Class Classification for Automated OAR Contour Assessment by Yihao Zhao BSc, Cuiyun Yuan MSc, Ying Liang PhD, Yang Li MSc, Chunxia Li MSc, Man Zhao MSc, Jun Hu PhD, Ningze Zhong Bsc, Wei Liu PhD, Chenbin Liu PhD

“…However, an effective QA process for these automatic contours remains an unmet need in clinical practice. …”
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Optimizing flood resilience in China’s mountainous areas: Design flood estimation using advanced machine learning techniques by Xuemei Wang, Ronghua Liu, Chaoxing Sun, Xiaoyan Zhai, Liuqian Ding, Xiao Liu, Xiaolei Zhang

“…Study region: China Study focus: We developed machine learning (ML) models for design flood estimation in mountainous catchments (≤ 500 km²) across China. This process considered different ML algorithms (random forest, extreme gradient boosting, and support vector regression), model scopes (nation and hydrological zones), and feature input sets (1–14 features) to optimize model development strategies. …”
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Engineered circular RNA-based DLL3-targeted CAR-T therapy for small cell lung cancer by Jingsheng Cai, Zheng Liu, Shaoyi Chen, Jingwei Zhang, Haoran Li, Xun Wang, Feng Yang, Shaodong Wang, Xiao Li, Yun Li, Kezhong Chen, Jun Wang, Ming Sun, Mantang Qiu

“…Using circRNA to construct transient Chimeric Antigen Receptor (CAR)-T cells can mitigate the limitations of conventional viral vector-based CAR-T approaches, such as complex process and long-term side effects. …”
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Non-destructive detection of pre-incubated chicken egg fertility using hyperspectral imaging and machine learning by Md Wadud Ahmed, Asher Sprigler, Jason Lee Emmert, Ryan N Dilger, Girish Chowdhary, Mohammed Kamruzzaman

“…Different spectral pre-processing and important feature selection methods were assessed for robust prediction model development. …”
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Gender Classification From Pashto Handwritten Text Images by Khan Sultan, Riaz Ahmad, Siraj Muhammad, Sulaiman Almutairi, Mohammed Abohashrh, Khalil Ullah, Abdallah Namoun, Ibrar Hussain

“…Computer vision (CV) is a subfield of computer science that enables machines to perceive, interpret, and understand visual data. It combines image processing, analysis, and machine learning to extract meaningful insights from images and videos. …”
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Region-wise landmarks-based feature extraction employing SIFT, SURF, and ORB feature descriptors to recognize Monozygotic twins from 2D/3D Facial Images [version 2; peer review: 2... by Srikanth Prabhu, Vinod Nayak, Aparna Jayakala, Krishna Prakasha K, Gangothri Sanil

“…Background In computer vision and image processing, face recognition is increasingly popular field of research that identifies similar faces in a picture and assigns a suitable label. …”
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Artificial Intelligence Driven Smart Farming for Accurate Detection of Potato Diseases: A Systematic Review by Avneet Kaur, Gurjit S. Randhawa, Farhat Abbas, Mumtaz Ali, Travis J. Esau, Aitazaz A. Farooque, Rajandeep Singh

“…The most widely used algorithms incorporate Support Vector Machine (SVM), Random Forest (RF), Convolutional Neural Network (CNN), and MobileNet with accuracy rates between 64.3 and 100%. …”
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Enhancing neuromolecular imaging classification in low-data regimes with generative machine learning: A case study in HDAC PET/MR imaging of alcohol use disorder by Tyler N. Meyer, Olga Andreeva, Roger D. Weiss, Wei Ding, Iris Shen, Changning Wang, Ping Chen, Tewodros Mulugeta Dagnew

“…These were used to train and test ML classifiers, including Support Vector Machine (SVM), XGBoost, and Random Forest, under leave-one-out cross-validation. …”
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COVID-19 Outbreak at Sports Club: Conditions of Occurrence and Causes of the Spread of Infection by A. A. Golubkova, T. A. Platonova, S. S. Smirnova, K. S. Komissarova, K. V. Varchenko

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Induction of Senescence in Lung Cancer Cells by Qidongning Formula via the Transcription Factor EGR1 by Di Zhou MD, Wen-Xiao Yang MD, Cheng-Yan Wang MD, Cheng-Xin Qian MM, Ling Xu PhD, Chang-Sheng Dong PhD, Jie Chen MM, Ya-Bin Gong PhD

“…A rescue assay using an EGR1-overexpressing vector to explore whether EGR1 is a key target gene of QDF-induced lung cancer senescence. …”
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A dual-task segmentation network based on multi-head hierarchical attention for 3D plant point cloud by Dan Pan, Baijing Liu, Lin Luo, An Zeng, Yuting Zhou, Kaixin Pan, Zhiheng Xian, Yulun Xian, Yulun Xian, Licheng Liu

“…Also, the dual-task framework employs Multi-Value Conditional Random Field (MV-CRF) to enable semantic segmentation of stem-leaf and individual leaf identification through the DSN architecture when processing manually-annotated 3D point cloud data. The network features a dual-branch architecture: one branch predicts the semantic class of each point, while the other embeds points into a high-dimensional vector space for instance clustering. …”
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Integrating image segmentation and auxiliary data for efficient estimation of FVC and AGB by Xifeng Zhang, Lu Xu, Yaxiao Li, Ying Yang, Jianguo Li, Hongyuan Ma

“…Abstract:: Accurate estimation of fractional vegetation cover (FVC) and aboveground biomass (AGB) is essential for large-scale grassland monitoring. However, this process is often constrained by the labor-intensive nature of field surveys. …”
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Characterization of microbiota signatures in Iberian pig strains using machine learning algorithms by Lamiae Azouggagh, Noelia Ibáñez-Escriche, Marina Martínez-Álvaro, Luis Varona, Joaquim Casellas, Sara Negro, Cristina Casto-Rebollo

“…The classification of the two Iberian strains reached the highest mean AUROC of 0.83 using Support Vector Machine (SVM) model. The most relevant genera in this classification performance were Acetitomaculum, Butyricicoccus and Limosilactobacillus. …”
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Tumor infection with human herpes viruses and features of peripheral blood lymphocyte subset composition in patients with uveal melanoma by Elena V. Svetlova, N. V. Balatskaya, I. G. Kulikova, S. V. Saakyan, I. V. Svirina, A. E. Andryushin, E. B. Myakoshina

“…Commercial test-systems of “Vector-Best” (Russia) were used for rt-PCR staging. …”
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Medida de similitud basada en saliencia by Sergio Domínguez

“…In this work a new proposal for evaluating similarity between two images is introduced; both images are represented by respective feature vectors, and the perceptual cue used to generate the similarity measure is saliency, a concept thoroughly known in Psychology. …”
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Identifying leptospirosis hotspots in Selangor: uncovering climatic connections using remote sensing and developing a predictive model by Muhammad Akram Ab Kadir, Rosliza Abdul Manaf, Siti Aisah Mokhtar, Luthffi Idzhar Ismail

“…Machine learning algorithms, including support vector machine (SVM), Random Forest (RF), and light gradient boosting machine (LGBM) were employed to develop predictive models for leptospirosis hotspot areas. …”
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ATP6AP1 drives pyroptosis-mediated immune evasion in hepatocellular carcinoma: a machine learning-guided therapeutic target by Lei Tang, Xiyue Wang, Zhengzheng Xia, Jiayu Yan, Shanshan Lin

“…Results Through a rigorous multi-algorithm screening process, ATP6AP1 was found to be a highly reliable biomarker with an area under the curve (AUC) of 0.979. …”
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Research and analysis of differential gene expression in CD34 hematopoietic stem cells in myelodysplastic syndromes. by Min-Xiao Wang, Chang-Sheng Liao, Xue-Qin Wei, Yu-Qin Xie, Peng-Fei Han, Yan-Hui Yu

“…After comprehensive evaluation, we ultimately selected three algorithms-Lasso regression, random forest, and support vector machine (SVM)-as our core predictive models. …”
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