Showing 441 - 460 results of 3,333 for search 'more node', query time: 0.10s Refine Results
  1. 441

    Surveillance and Surgical Salvage Treatment for Endoscopically Removed T1 Colorectal Cancers by Hiroyuki Takamaru, Cynthia Tsay, Yutaka Saito

    Published 2025-07-01
    “…Endoscopic submucosal dissection (ESD) enables <em>en-bloc</em> resection of large lesions more than 20 mm in size. Therefore, the use of ESD has gained broader acceptance for clinical applications globally. …”
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  2. 442

    UPN-GCN: Update Positive-Negative Graph Convolution Neural Network in Non-Euclidean Structured Data by Lijun Fan, Shichao Yi, Wenrui Guan, Pingxin Wang

    Published 2025-01-01
    “…However, this positive-negative relationship does not accurately reflect the differences and similarities between data, thereby reducing the accuracy of node classification. Therefore, we have designed a new convolutional neural network model UPN-GCN based on updating positive and negative graphs. …”
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  3. 443
  4. 444

    Multi-stage bidirectional informed-RRT * plant protection UAV path planning method based on A * algorithm domain guidance by Jian Li, Jian Li, Yuan Gao, Yuan Gao, Zheng Li, Zheng Li, Weijian Zhang, Weijian Zhang, Weilin Yu, Weilin Yu, Yating Hu, He Liu, Changtian Li

    Published 2025-08-01
    “…Experimental results show that, compared to traditional RRT* and its improved variants, the proposed algorithm reduces computation time by 56.3%–92.5% and shortens path length by 0.42%–8.5%, while also demonstrating superior path smoothness and feasibility, as well as a more balanced distribution of search nodes. Comprehensive analysis indicates that the A*-MSRRT* (A*-Guided Multi-stage Bidirectional Informed-RRT*) algorithm has strong potential for application in complex agricultural environments.…”
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  5. 445

    Association of Survival with Radiologic-Pathologic Discordance in Patients with Hepatocellular Carcinoma: A Nationwide Cohort Study Based on the Primary Liver Cancer Registry in Ko... by Woo Sun Rou, Hong Jae Jeon, Hyuk Soo Eun, Hyun Seok Lee, Jae Ho Park, Jong Seok Joo, Ju Seok Kim, Eaum Seok Lee, Seok Hyun Kim, Jeong Eun Lee, Kyung Sook Shin, Seok-Hwan Kim, Min-Kyung Yeo, Ju-Mi Lee, In Sun Kwon, Byung Seok Lee

    Published 2025-07-01
    “…In multivariate analyses, radiologicpathologic discrepancies in more than two factors (hazard ratio [HR], 3.251) and vascular invasion (HRs, 2.044 and 2.596), and lymph node metastasis (HRs, 8.157 and 7.209) on pathology or both imaging and pathology, respectively, were independent predictors of survival (all p<0.001). …”
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  6. 446
  7. 447

    Comparative analysis and optimization of tumor regression grade assessment systems in neoadjuvant therapy for esophageal squamous cell carcinoma by Qiao Yang, Xiaoqing Zhou, Jiayu Li, Jieyu Wang, Jingcheng Luo, Dan Luo, Lin Shi, Chengmin Zhou, Yi Wang, Xuefeng Leng, Qifeng Wang, Yang Liu, Yehan Zhou

    Published 2025-08-01
    “…These findings may assist clinicians in more accurately assessing patient prognosis and adjusting treatment strategies accordingly, ultimately optimizing patient treatment pathways.…”
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  8. 448

    Histopathological Characteristics – Immediate Prognostic Factors for Left Colon Cancer by Madi MARINCA, Mircea BEURAN

    Published 2020-03-01
    “…Conclusions: The incidence of lymphatic metastases differs according to the histopathological type of the tumor, the tubulovillous adenoma being more frequently associated with lymphatic metastases; distal metastases are more frequently seen in patients in the rural areas, based on the low addressability and accessibility to medical services. …”
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  9. 449
  10. 450

    HEAD AND NECK SQUAMOUS CELL CARCINOMA DEPENDING ON THE MORPHOLOGICAL CHARACTERISTICS OF THE PRIMARY TUMOR by V. A. Bychkov, L. N. Bondar, E. L. Choynzonov, V. M. Perelmuter

    Published 2017-06-01
    “…Single tumor cells and structures formed by polymorphic cells were observed in primary tumor more often in the patients with metastatic lymph nodes than in patients with intact lymph nodes. …”
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  11. 451
  12. 452

    PLGNN: graph neural networks via adaptive feature perturbation and high-way links by Meixia He, Peican Zhu, Yang Liu, Keke Tang

    Published 2025-05-01
    “…However, inevitable missing information in graph networks hinders GNNs from aggregating more abundant feature information, limiting GNNs’ performance. …”
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  13. 453

    A population‐based analyses of the evolving management of cN1M0 prostate cancer in the PSMA‐PET era by Jennifer Ward, Kevin Armstrong, Therese Min‐Jung Kang, Jodie Tham, Yuan‐Hong Lin, Marcus Cheng, Jeremy Grummet, Nathan Lawrentschuk, Marlon Perera, Shomik Sengupta, David Chang, Michael Ng, Jonathan Bensley, Michelle Steeper, Krupa Krishnaprasad, Maggie Johnson, Nikolajs Zeps, Jeremy Millar, Wee Loon Ong

    Published 2025-07-01
    “…Abstract Objectives To evaluate the patterns of management of clinical node‐positive non‐metastatic prostate cancer (cN1M0PC) at a population‐based level over time, and to identify factors associated with the different management approaches. …”
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  14. 454

    Multifocal metastatic papillary thyroid carcinoma: a case report and literature review by S. Sheptukha, V. Khoperiya, O. Mostiuk, V. Kolotusha

    Published 2025-03-01
    “…The presence of vascular, extra-organic invasion and metastases necessitate the selection of more aggressive treatment and monitoring. Materials and methods. …”
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  15. 455

    Adaptive DecayRank: Real-Time Anomaly Detection in Dynamic Graphs with Bayesian PageRank Updates by Ocheme Anthony Ekle, William Eberle, Jared Christopher

    Published 2025-03-01
    “…Our method extends the dynamic PageRank algorithm by incorporating an adaptive Bayesian updating mechanism, allowing nodes to dynamically adjust their decay factors based on observed graph changes. …”
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  16. 456

    Merkel Cell Carcinoma of the Skin: Deducing the Pattern of Spread from an International Aggregated Database of 949 Patients by Patricia Tai, Kurian Joseph, Vimal H. Prajapati, Aoife Jones Thachuthara, Jidong Lian, Avi Assouline, Edward Yu, Michael Veness

    Published 2025-04-01
    “…The primary outcome was recurrence patterns. (3) Results: (a) More patients presented with lymph node metastases (LNMs) than DMs at diagnosis: 17.9% (166 among the 929 patients with known staging) vs. 1.9% (18/929); (b) 310/929 (33.4%) developed lifetime DM, of whom 220/310 also developed LNM. …”
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  17. 457
  18. 458

    Preoperative predictors of endometrial carcinoma in patients undergoing hysterectomy for endometrial intraepithelial neoplasia by Neçirvan Çağdaş Çaltek, Hale Özer Çaltek, Mahmut Yassa, Gazi Güner, İlteriş Yaman, İlkbal Temel Yüksel

    Published 2025-05-01
    “…Abstract Objective Patients undergoing surgery for endometrial intraepithelial neoplasia (EIN) have a high likelihood of concurrent endometrial cancer (EC). Lymph node dissection (LND) may be required during the operation. …”
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  19. 459

    Postoperative Lymphatic Leakage in Oncosurgical Patients by I. V. Yarema, O. E. Fatuev, N. S. Kozlov, A. G. Tagirova, I. M. Vagabova, A. Sh. Hasan, R. A. Simanin, G. M. Korolyuk, V. V. Safronova

    Published 2019-04-01
    “…The results of treatment of 310 patients subjected to standard elective surgical intervention for a malignant pathology of different organs with regional lymph node dissection were evaluated. The selection criterion was prolonged (more than 7 days) and prominent (over 50 ml a day) lymphatic leakage during the postoperative period. …”
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  20. 460

    Comparative evaluation of TNM staging systems (eighth vs. ninth edition) for the non-surgical treatment of localized and locally advanced anal squamous cell carcinoma: Prognostic s... by Aihong Zheng, Hong'en Xu, Yiming Tao, Bingchen Chen, Jieni Ding, Tao Song, Yanwei Lu

    Published 2025-01-01
    “…This study aims to compare the survival discrimination of the Tumor-Node-Metastasis (TNM) eighth and ninth editions for patients with localized and locally advanced (LLA) anal squamous cell carcinoma (ASCC) treated non-surgically and to evaluate the prognostic impact of T classification and lymph node (LN) status with data from the Surveillance, Epidemiology, and End Results database. …”
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