Showing 441 - 460 results of 1,135 for search 'T13 (classification)', query time: 0.06s Refine Results
  1. 441
  2. 442
  3. 443
  4. 444

    Dataset for comparative analysis of precision metagenomics and traditional methods in urinary tract infection diagnosticsNCBI by Rob E. Carpenter, Sadia Almas, Vaibhav K. Tamrakar, Rahul Sharma

    Published 2025-04-01
    “…The dataset includes 47 urine samples, each analyzed by microbial culture, PCR, and precision metagenomics, followed by bioinformatic classification using the Explify® platform. precision metagenomics identified significantly more uropathogens (62 distinct organisms) compared to PCR (19 organisms) and microbial culture (13 organisms), with 98 % of samples testing positive for polymicrobial infections via precision metagenomics. …”
    Get full text
    Article
  5. 445
  6. 446
  7. 447
  8. 448

    Perceived MOOC satisfaction: A review mining approach using machine learning and fine-tuned BERTs by Xieling Chen, Haoran Xie, Di Zou, Gary Cheng, Xiaohui Tao, Fu Lee Wang

    Published 2025-06-01
    “…The study uses a MOOC corpus containing 102,184 course reviews from 401 courses across 13 disciplines. The methodology involves three approaches: (1) machine learning for automatic classification of review helpfulness, (2) BERT models for automatic classification of review topics, and (3) multiple linear regression analysis to explore the factors influencing learner satisfaction. …”
    Get full text
    Article
  9. 449
  10. 450

    Are the Menstrual Characteristics Similar in Adolescent and Adult Women with Cerebral Palsy? by Hanife Dogan, Duygu Turker, Ozge Coban, Merve Basol Goksuluk, Nuriye Ozengin, Necmiye Un Yildirim

    Published 2023-03-01
    “…Gross motor function levels of women with cerebral palsy were determined by gross motor function classification system expanded and revised. Menstrual-health characteristics were evaluated with a self-report questionnaire. …”
    Get full text
    Article
  11. 451

    Diagnosis of Schizophrenia and Its Subtypes Using MRI and Machine Learning by Hosna Tavakoli, Reza Rostami, Reza Shalbaf, Mohammad‐Reza Nazem‐Zadeh

    Published 2025-01-01
    “…Finding The classification accuracy reached as high as 79% in distinguishing schizophrenia patients from healthy in the UCLA dataset. …”
    Get full text
    Article
  12. 452
  13. 453
  14. 454
  15. 455
  16. 456
  17. 457
  18. 458
  19. 459
  20. 460