Showing 8,561 - 8,580 results of 26,849 for search 'evaluation computing', query time: 0.19s Refine Results
  1. 8561

    Designing AI-powered translation education tools: a framework for parallel sentence generation using SauLTC and LLMs by Moneerh Aleedy, Fatma Alshihri, Souham Meshoul, Maha Al-Harthi, Salwa Alramlawi, Badr Aldaihani, Hadil Shaiba, Eric Atwell

    Published 2025-03-01
    “…Translation education (TE) demands significant effort from educators due to its labor-intensive nature. Developing computational tools powered by artificial intelligence (AI) can alleviate this burden by automating repetitive tasks, allowing instructors to focus on higher-level pedagogical aspects of translation. …”
    Get full text
    Article
  2. 8562
  3. 8563
  4. 8564
  5. 8565

    Deep5mC: Predicting 5-methylcytosine (5mC) methylation status using a deep learning transformer approach by Evan Kinnear, Houssemeddine Derbel, Zhongming Zhao, Qian Liu

    Published 2025-01-01
    “…Genomic 5mC is not randomly distributed but exhibits a strong association with genomic sequences. Thus, various computational methods were developed to predict 5mC status based on DNA sequences. …”
    Get full text
    Article
  6. 8566
  7. 8567

    Optimized CNN-Bi-LSTM–Based BCI System for Imagined Speech Recognition Using FOA-DWT by Meenakshi Bisla, Radhey Shyam Anand

    Published 2024-01-01
    “…Speech imagery is emerging as a significant neuro-paradigm for designing an electroencephalography (EEG)-based brain–computer interface (BCI) system for the purpose of rehabilitation, medical neurology, and to aid people with disabilities in interacting with their surroundings. …”
    Get full text
    Article
  8. 8568
  9. 8569
  10. 8570
  11. 8571

    Struct2SL: Synthetic lethality prediction based on AlphaFold2 structure information and Multilayer Perceptron by Yurui Huang, Ruzhe Yuan, Yaxuan Li, Zheming Xing, Junyi Li

    Published 2025-01-01
    “…In cancer therapeutics, the elucidation of synthetic lethality principles introduces transformative concepts for devising novel treatment paradigms. Computational methods to predict synthetic lethal (SL) gene pairs have potential to markedly enhance the precision and efficacy of cancer interventions. …”
    Get full text
    Article
  12. 8572
  13. 8573

    CFSAN SNP Pipeline 2 (CSP2): a pipeline for fast and accurate SNP distance estimation from bacterial genome assemblies by Robert Literman, Jayanthi Gangiredla, Hugh Rand, James B. Pettengill

    Published 2025-07-01
    “…Background Accurate genetic distance estimation from pathogen whole-genome sequence data is critical for public health surveillance, and with respect to food safety it provides crucial information within traceback and outbreak investigations. The computational demands required for contemporary bioinformatics pipelines to extract high resolution single nucleotide polymorphisms (SNPs) grow in parallel with the size of pathogen clusters, where single strains of common pathogens such as Escherichia coli and Salmonella enterica can now contain hundreds or thousands of isolates. …”
    Get full text
    Article
  14. 8574
  15. 8575
  16. 8576
  17. 8577
  18. 8578

    Deep learning of pretreatment multiphase CT images for predicting response to lenvatinib and immune checkpoint inhibitors in unresectable hepatocellular carcinoma by Nan-Qing Liao, Zhu-Jian Deng, Wei Wei, Jia-Hui Lu, Min-Jun Li, Liang Ma, Qing-Feng Chen, Jian-Hong Zhong

    Published 2024-12-01
    “…We developed an interpretable deep learning model using multiphase computed tomography (CT) images to predict whether patients will respond or not to CLICI treatment, based on the Response Evaluation Criteria in Solid Tumors, version 1.1 (RECIST v1.1). …”
    Get full text
    Article
  19. 8579
  20. 8580