Showing 81 - 100 results of 1,658 for search '"Pathology"', query time: 0.08s Refine Results
  1. 81
  2. 82

    Enhancement of CD8+T cell cytotoxicity activity by IFN-α implies alternative pathologic role in systemic lupus erythematosus by Chen-xing Zhang, You-ying Mao, Yu-pin Tan, Mei-yu Zhang, Kang Shao, Shu-jun Wang, Ping Ji, Jia-yuan Wang, Lei Yin, Ying Wang

    Published 2025-06-01
    “…In the present study, we aimed to explore the pathologic role of IFN-α in regard to dysfunction of CD8+T cells in SLE. …”
    Get full text
    Article
  3. 83

    The Treatment Effect of Plantago Major on Lung Cancer Based on the Computed Tomography and Pathological Findings: A Case Report Study by Saade Abdalkareem Jasim, Bashar Mudhaffar Abdullah, Patricio Yánez-Moretta, Wesam R. Kadhum, Yasser Fakri Mustafa, Enas R. Alwaily, Munther Abosoda, Ali Alsalamy, Sada Ghalib Al-Musawi, Alaa A. Omran

    Published 2025-01-01
    “…Here, we introduced a patient having lung cancer proved by Computed Tomography (CT) and pathological findings. The treatment effect of PM was assessed and presented based on CT and laboratory examinations for this patient as a first human case study. …”
    Get full text
    Article
  4. 84

    Atlas of Clinical Dermatology / by Du Vivier, Anthony

    Published 1993
    View in OPAC
    Book
  5. 85
  6. 86
  7. 87

    The impact of apolipoprotein E, type ∊4 allele on Alzheimer's disease pathological biomarkers: a comprehensive post-mortem pilot-analysis. by Ziyu Wan, Tao Ma

    Published 2025-01-01
    “…Remarkably, the phosphorylation of tau observed in neurofibrillary tangles (NFTs) marked by the AT8 antibody, emerges as the most correlated factor with other pathological biomarkers. This correlation is mediated by both tau and amyloid pathology, suggesting a higher hierarchical role in determining AD pathological effects than other biomarkers. …”
    Get full text
    Article
  8. 88

    A Retrospective Analysis of Thymoma: Clinical Radiological Pathological Features and Treatment Modalities – Insights from a Tertiary Care Center by A. Vasudevan, Keerthi Prakash, Ajay Narasimhan, R. Sridhar, R. Narasimhan, C Ganapathy Arumugam

    Published 2025-01-01
    “…This study aimed to analyze the clinical, radiological, and pathological characteristics and treatment modalities of thymoma cases at our institute. …”
    Get full text
    Article
  9. 89
  10. 90
  11. 91
  12. 92
  13. 93
  14. 94
  15. 95
  16. 96
  17. 97
  18. 98

    Enhanced preoperative prediction of breast lesion pathology, prognostic biomarkers, and molecular subtypes using multiple models diffusion-weighted MR imaging by Litong He, Feng Li, Yanjin Qin, Yuling Li, Qilan Hu, Zhiqiang Liu, Yunfei Zhang, Tao Ai

    Published 2025-02-01
    “…We retrospectively analyzed 132 patients with pathologically verified breast lesions (41 benign and 91 malignant) who underwent a full protocol preoperative breast MRI protocol, including a diffusion-weighted imaging (DWI) sequence with nine b values (0 to 2000 s/mm2) on a 3.0T MR scanner. …”
    Get full text
    Article
  19. 99

    Sistem Deteksi Myocardial Infarction Berdasarkan Pathological Q Waves Dan ST Segment Elevation Menggunakan Metode Support Vector Machine by Ragil Hadi Prasetyo, Edita Rosana Widasari, Agung Setia Budi

    Published 2022-12-01
    “…Penelitian ini melakukan deteksi Myocardial Infarction berdasarkan 2 kondisi sinyal abnormal yaitu Pathological Q Waves dan ST Segment Elevation. Kedua kondisi sinyal abnormal tersebut dapat digunakan untuk mendeteksi Myocardial Infarction. …”
    Get full text
    Article
  20. 100

    Machine learning analysis of pathological images to predict 1-year progression-free survival of immunotherapy in patients with small-cell lung cancer by Hirotaka Matsumoto, Hiroaki Akamatsu, Nobuyuki Yamamoto, Yuki Sato, Daichi Fujimoto, Yoshihiko Taniguchi, Motohiro Tamiya, Yasuhiro Koh, Junya Fukuoka, Hisashi Tanaka, Naoki Furuya, Ryota Shibaki, Tsukasa Nozawa, Akira Sano, Yuka Kitamura, Takashi Kijima, Toshihide Yokoyama, Satoru Miura, Akito Hata, Jun Sugisaka

    Published 2024-02-01
    “…The primary outcome was the mean area under the curve (AUC) of machine learning models in predicting the 1-year PFS.Results We analyzed 100,544 patches of pathological images from 78 patients. The mean AUC values of patient information, pathological image, and combined models were 0.789 (range 0.571–0.982), 0.782 (range 0.750–0.911), and 0.868 (range 0.786–0.929), respectively. …”
    Get full text
    Article