Showing 63,401 - 63,420 results of 64,539 for search '"algorithm"', query time: 0.29s Refine Results
  1. 63401

    Apple Yield Estimation Method Based on CBAM-ECA-Deeplabv3+ Image Segmentation and Multi-Source Feature Fusion by Wenhao Cui, Yubin Lan, Jingqian Li, Lei Yang, Qi Zhou, Guotao Han, Xiao Xiao, Jing Zhao, Yongliang Qiao

    Published 2025-05-01
    “…Yield estimation models were constructed using k-nearest neighbors (KNN), partial least squares (PLS), random forest (RF), and support vector machine (SVM) algorithms under both single feature sets and combined feature sets (including vegetation indices, structural feature ratios, SPAD, vegetation indices + SPAD, vegetation indices + structural feature ratios, structural feature ratios + SPAD, and the combination of all three). …”
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  2. 63402

    From smoking cessation to physical activity: Can ontology-based methods for automated evidence synthesis generalise across behaviour change domains? [version 2; peer review: 2 appr... by Candice Moore, Emily Hayes, Oscar Castro, Ella Howes, Alison J Wright, Emma Norris, Susan Michie, Robert West

    Published 2025-03-01
    “…The Human Behaviour-Change Project (HBCP) aims to improve evidence synthesis in behavioural science by compiling intervention reports and annotating them with an ontology to train information extraction and prediction algorithms. The HBCP used smoking cessation as the first ‘proof of concept’ domain but intends to extend its methodology to other behaviours. …”
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    Article
  3. 63403

    Construction of mitochondrial signature (MS) for the prognosis of ovarian cancer by Miao Ao, You Wu, Kunyu Wang, Haixia Luo, Wei Mao, Anqi Zhao, Xiaomeng Su, Yan Song, Bin Li

    Published 2025-07-01
    “…After univariate Cox analysis, prognostic genes were carried out for modeling mitochondria signature (MS) based on 101 combinations of 10 machine learning algorithms. Functional enrichment analysis was performed on this prognostic gene set. …”
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  4. 63404

    The Impact of the Natural Grass-Growing Model on the Development of Korla Fragrant Pear Fruit, as Well as Its Influence on Post-Harvest Sugar Metabolism and the Expression of Key E... by Mingyang Yu, Lanfei Wang, Yan Chen, Weifan Fan, Hao Wang, Kailu Guo, Shutian Tao, Xin Gong, Jianping Bao

    Published 2025-04-01
    “…A classification model was constructed using machine learning algorithms (RF, KNN, SVM), and particle swarm optimization (PSO) was employed to identify key factors. …”
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  5. 63405
  6. 63406

    First M87 Event Horizon Telescope Results. VI. The Shadow and Mass of the Central Black Hole by The Event Horizon Telescope Collaboration, Kazunori Akiyama, Antxon Alberdi, Walter Alef, Keiichi Asada, Rebecca Azulay, Anne-Kathrin Baczko, David Ball, Mislav Baloković, John Barrett, Dan Bintley, Lindy Blackburn, Wilfred Boland, Katherine L. Bouman, Geoffrey C. Bower, Michael Bremer, Christiaan D. Brinkerink, Roger Brissenden, Silke Britzen, Avery E. Broderick, Dominique Broguiere, Thomas Bronzwaer, Do-Young Byun, John E. Carlstrom, Andrew Chael, Chi-kwan Chan, Shami Chatterjee, Koushik Chatterjee, Ming-Tang Chen, Yongjun Chen, Ilje Cho, Pierre Christian, John E. Conway, James M. Cordes, Geoffrey B. Crew, Yuzhu Cui, Jordy Davelaar, Mariafelicia De Laurentis, Roger Deane, Jessica Dempsey, Gregory Desvignes, Jason Dexter, Sheperd S. Doeleman, Ralph P. Eatough, Heino Falcke, Vincent L. Fish, Ed Fomalont, Raquel Fraga-Encinas, Per Friberg, Christian M. Fromm, José L. Gómez, Peter Galison, Charles F. Gammie, Roberto García, Olivier Gentaz, Boris Georgiev, Ciriaco Goddi, Roman Gold, Minfeng Gu, Mark Gurwell, Kazuhiro Hada, Michael H. Hecht, Ronald Hesper, Luis C. Ho, Paul Ho, Mareki Honma, Chih-Wei L. Huang, Lei Huang, David H. Hughes, Shiro Ikeda, Makoto Inoue, Sara Issaoun, David J. James, Buell T. Jannuzi, Michael Janssen, Britton Jeter, Wu Jiang, Michael D. Johnson, Svetlana Jorstad, Taehyun Jung, Mansour Karami, Ramesh Karuppusamy, Tomohisa Kawashima, Garrett K. Keating, Mark Kettenis, Jae-Young Kim, Junhan Kim, Jongsoo Kim, Motoki Kino, Jun Yi Koay, Patrick M. Koch, Shoko Koyama, Michael Kramer, Carsten Kramer, Thomas P. Krichbaum, Cheng-Yu Kuo, Tod R. Lauer, Sang-Sung Lee, Yan-Rong Li, Zhiyuan Li, Michael Lindqvist, Kuo Liu, Elisabetta Liuzzo, Wen-Ping Lo, Andrei P. Lobanov, Laurent Loinard, Colin Lonsdale, Ru-Sen Lu, Nicholas R. MacDonald, Jirong Mao, Sera Markoff, Daniel P. Marrone, Alan P. Marscher, Iván Martí-Vidal, Satoki Matsushita, Lynn D. Matthews, Lia Medeiros, Karl M. Menten, Yosuke Mizuno, Izumi Mizuno, James M. Moran, Kotaro Moriyama, Monika Moscibrodzka, Cornelia Müller, Hiroshi Nagai, Neil M. Nagar, Masanori Nakamura, Ramesh Narayan, Gopal Narayanan, Iniyan Natarajan, Roberto Neri, Chunchong Ni, Aristeidis Noutsos, Hiroki Okino, Héctor Olivares, Tomoaki Oyama, Feryal Özel, Daniel C. M. Palumbo, Nimesh Patel, Ue-Li Pen, Dominic W. Pesce, Vincent Piétu, Richard Plambeck, Aleksandar PopStefanija, Oliver Porth, Ben Prather, Jorge A. Preciado-López, Dimitrios Psaltis, Hung-Yi Pu, Venkatessh Ramakrishnan, Ramprasad Rao, Mark G. Rawlings, Alexander W. Raymond, Luciano Rezzolla, Bart Ripperda, Freek Roelofs, Alan Rogers, Eduardo Ros, Mel Rose, Arash Roshanineshat, Helge Rottmann, Alan L. Roy, Chet Ruszczyk, Benjamin R. Ryan, Kazi L. J. Rygl, Salvador Sánchez, David Sánchez-Arguelles, Mahito Sasada, Tuomas Savolainen, F. Peter Schloerb, Karl-Friedrich Schuster, Lijing Shao, Zhiqiang Shen, Des Small, Bong Won Sohn, Jason SooHoo, Fumie Tazaki, Paul Tiede, Remo P. J. Tilanus, Michael Titus, Kenji Toma, Pablo Torne, Tyler Trent, Sascha Trippe, Shuichiro Tsuda, Ilse van Bemmel, Huib Jan van Langevelde, Daniel R. van Rossum, Jan Wagner, John Wardle, Jonathan Weintroub, Norbert Wex, Robert Wharton, Maciek Wielgus, George N. Wong, Qingwen Wu, André Young, Ken Young, Ziri Younsi, Feng Yuan, Ye-Fei Yuan, J. Anton Zensus, Guangyao Zhao, Shan-Shan Zhao, Ziyan Zhu, Joseph R. Farah, Zheng Meyer-Zhao, Daniel Michalik, Andrew Nadolski, Hiroaki Nishioka, Nicolas Pradel, Rurik A. Primiani, Kamal Souccar, Laura Vertatschitsch, Paul Yamaguchi

    Published 2019-01-01
    “…We develop and fit geometric crescent models (asymmetric rings with interior brightness depressions) using two independent sampling algorithms that consider distinct representations of the visibility data. …”
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  7. 63407
  8. 63408

    Comprehensive profiling of chemokine and NETosis-associated genes in sarcopenia: construction of a machine learning-based diagnostic nomogram by Yingwei Wang, Le Wang, Yan Zhang, Minghui Wang, Huaying Zhao, Cheng Huang, Huaiyang Cai, Shuangyang Mo

    Published 2025-06-01
    “…Two machine learning algorithms and univariate analysis were integrated to screen signature genes, which were subsequently used to construct diagnostic nomogram models for sarcopenia. …”
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    Article
  9. 63409

    Novel multi-omics analysis revealing metabolic heterogeneity of breast cancer cell and subsequent development of associated prognostic signature by Peng Zhang, Cuicui Li, Fen Li, Jiezhong Wu, Kunpeng Hu, He Huang

    Published 2025-09-01
    “…A metabolic risk signature was constructed using machine learning algorithms. Immune cell infiltration and immune checkpoint profiles were assessed to explore tumor microenvironment differences. …”
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    Article
  10. 63410

    GIRAFE v1: a global climate data record for precipitation accompanied by a daily sampling uncertainty by H. Konrad, R. Roca, A. Niedorf, S. Finkensieper, M. Schröder, S. Cloché, G. Panegrossi, P. Sanò, C. Kidd, C. Kidd, R. A. Jucá Oliveira, R. A. Jucá Oliveira, K. Fennig, T. Sikorski, M. Lemoine, R. Hollmann

    Published 2025-08-01
    “…GIRAFE is based on precipitation rate estimates obtained from observations by a variety of passive microwave (PMW) radiometers on board low-Earth orbit satellites and related retrieval algorithms and frequent and highly resolved infrared observations from geostationary satellites covering all longitudes and used at latitudes below 55° N/S. …”
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  11. 63411
  12. 63412

    Investigating Transcriptional Age Acceleration in Inflammatory Skin Diseases by Richie Jeremian, Melissa Galati, Rayyan Fotovati, Kaiyang Li, Carolyn Jack, David O. Croitoru, Stephan Caucheteux, Philippe Lefrançois, Vincent Piguet

    Published 2025-09-01
    “…We investigated the role of transcriptional clocks in patients with hidradenitis suppurativa (n = 37), those with atopic dermatitis (n = 27), those with plaque psoriasis (n = 28), and healthy subjects (n = 38) using 7 clock algorithms, to improve the understanding of underlying pathophysiology and disease trajectory. …”
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    Article
  13. 63413

    Plot-Rice v1.0: A global plot-based rice benchmark dataset with spatiotemporal heterogeneity for scientific deep learning by Ji Ge, Hong Zhang, Wenjiang Huang, Zihuan Guo, Lu Xu, Yazhe Xie, Mingyang Song, Yinhaibin Ding, Chao Wang

    Published 2025-06-01
    “…The absence of a global, standardized satellite dataset for rice mapping benchmarking has long resulted in both substantial redundant data processing efforts and challenges in evaluating new algorithms under a unified benchmark. To address these deficiencies, this paper introduces Plot-Rice v1.0, a global heterogeneous rice benchmark dataset based on Sentinel-1 and Sentinel-2 images, along with an automated framework that integrates SAR temporal features and leverages the foundation image segmentation model SAM-2 to generate plot-level rice samples. …”
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    Article
  14. 63414

    Pre-treatment tumour PET metrics and clinical outcomes of anal cancer in patients living with and without HIV by Michael Pennock, N. Patrik Brodin, Christian Velten, Megi Gjini, Nitin Ohri, Chandan Guha, Shalom Kalnicki, Wolfgang A. Tome, Madhur K. Garg, Rafi Kabarriti

    Published 2025-04-01
    “…Pre-treatment PET metrics were calculated with semi-automatic gradient-based segmentation algorithms. Cox-proportional-hazard and Kaplan-Meier modelling were used to investigate tumour PET metrics and outcomes: overall survival (OS), progression-free survival (PFS), and locoregional control (LRC). …”
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    Article
  15. 63415

    Using electronic health records to enhance surveillance of diabetes in children, adolescents and young adults: a study protocol for the DiCAYA Network by Hui Zhou, Manmohan Kamboj, Yi Guo, Angela D Liese, Rebecca Anthopolos, Lu Zhang, John Chang, Anna Roberts, Tessa Crume, Brian E Dixon, Hui Shao, David C Lee, Lorna E Thorpe, Dimitri Christakis, Eneida A Mendonca, Katie Allen, Dana Dabelea, Giuseppina Imperatore, Mark Weiner, Meredith Akerman, Rong Wei, Kristi Reynolds, Annemarie G Hirsch, Jasmin Divers, Tianchen Lyu, Alex Ewing, Shaun Grannis, Yuan Luo, Bo Cai, Anthony Wong, Brian S Schwartz, Meda Pavkov, Meredith Lewis, Sarah Conderino, Jiang Bian, Yonghui Wu, Jihad S Obeid, Harold P Lehmann, Charles Bailey, Theresa Anderson, Elizabeth A Shenkman, Elizabeth Nauman, Christopher Forrest, Mattia Prosperi, Seho Park, Cara M Nordberg, Tessa L Crume, Anna Bellatorre, Stefanie Bendik, Marc Rosenman, Levon Utidjian, Mitch Maltenfort, Amy Shah, G Todd Alonso, Sara Deakyne-Davies, Tim Bunnell, Anne Kazak, Melody Kitzmiller, Daksha Ranade, Joseph J DeWalle, H Lester Kirchner, Dione G Mercer, Amy Poissant, Nimish Valvi, Jeff Warvel, Ashley Wiensch, Tamara Hannon, Eva Lustigova, Don McCarthy, Matthew T Mefford, George Lales, Allison Zelinski, Pedro Rivera, Thomas Carton, Victor W Zhong, Andrew Fair, Jessica Guillaume, Shahidul Islam, Alan Jacobson, Chinyere Okpara, Anand Rajan, Andrea Titus, Rebecca Conway, Toan Ong, Jack Pattee, Shawna Burgett, Bethlehem Shiferaw, Sarah J Bost, William T Donahoo, William R Hogan, Piaopiao Li, Lisa Knight, Caroline Rudisill, Jessica Stucker, Deborah Bowlby, Elaine Apperson, Deborah B Rolka

    Published 2024-01-01
    “…The network has two primary aims, namely: (1) to refine and validate EHR-based computable phenotype algorithms for accurate identification of type 1 and type 2 diabetes among youth and young adults and (2) to estimate the incidence and prevalence of type 1 and type 2 diabetes among youth and young adults and trends therein. …”
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  16. 63416

    Domain-Adaptive and Per-Fraction Guided Deep Learning Framework for Magnetic Resonance Imaging-Based Segmentation of Organs at Risk in Gynecologic Cancers by Reza Kalantar, PhD, Manasi Ingle, FRCR, Romelie Rieu, BA, BmBCh, Sebastian Curcean, MD, Jessica Mary Winfield, PhD, Gigin Lin, MD, PhD, Christina Messiou, MD, MRCP, FRCR, Susan Lalondrelle, FRCR, Dow-Mu Koh, MD, FRCP, FRCR, Matthew David Blackledge, PhD

    Published 2025-04-01
    “…Purpose: The integration of magnetic resonance imaging into radiation therapy (RT) treatment necessitates automated segmentation algorithms for fast and accurate adaptive interventions, particularly in magnetic resonance imaging-integrated linear accelerator (MR-linac or MRL) treatment systems. …”
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  17. 63417

    Toward Digital Twin of Off-Road Vehicles Using Robot Simulation Frameworks by Arianna Rana, Antonio Petitti, Angelo Ugenti, Rocco Galati, Giulio Reina, Annalisa Milella

    Published 2024-01-01
    “…The first one is based on Gazebo, an open-source 3D robotics simulator, to test and validate the algorithms developed in the ROS framework; the second one adopts the vehicle mechanical assembly in MSC Adams, a multibody modeling software used to study the dynamics of complex mechanical systems. …”
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  18. 63418

    Potassium Fulvate Alleviates Salinity and Boosts Oat Productivity by Modifying Soil Properties and Rhizosphere Microbial Communities in the Saline–Alkali Soils of the Qaidam Basin... by Jie Wang, Xin Jin, Xinyue Liu, Yunjie Fu, Kui Bao, Zhixiu Quan, Chengti Xu, Wei Wang, Guangxin Lu, Haijuan Zhang

    Published 2025-07-01
    “…We integrated three machine learning algorithms—least absolute shrinkage and selection operator (LASSO), Random Forest (RF), and eXtreme Gradient Boosting (XGBoost)—to minimize the bias inherent in any single method. …”
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  19. 63419

    Synthetic Data Generation and Evaluation Techniques for Classifiers in Data Starved Medical Applications by Wan D. Bae, Shayma Alkobaisi, Matthew Horak, Siddheshwari Bankar, Sartaj Bhuvaji, Sungroul Kim, Choon-Sik Park

    Published 2025-01-01
    “…However, prediction models are sensitive to the size and distribution of the data they are trained on. ML algorithms rely heavily on vast quantities of training data to make accurate predictions. …”
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  20. 63420

    Application of deep learning reconstruction at prone position chest scanning of early interstitial lung disease by Ruijie Zhao, Yun Wang, Jiaru Wang, Zixing Wang, Ran Xiao, Ying Ming, Sirong Piao, Jinhua Wang, Lan Song, Yinghao Xu, Zhuangfei Ma, Peilin Fan, Xin Sui, Wei Song

    Published 2025-08-01
    “…This study supported that DLR was promising for maintaining image quality under a lower radiation dose in prone scanning, and it offered valuable insights for the selection of images reconstruction algorithms for the diagnosis and follow-up of early ILD.…”
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