Showing 261 - 280 results of 288 for search '(( python consider implementing ) OR ( ((python model) OR (python code)) implementing ))', query time: 0.27s Refine Results
  1. 261

    Resistant & sensitive cell line Info on AZD5991. by Yang Wu (66682)

    Published 2025
    “…Our methods are implemented in Python and are freely available from GitHub (<a href="https://github.com/queryang/PASO" target="_blank">https://github.com/queryang/PASO</a>).…”
  2. 262

    Resistant & sensitive drug info on COLO800. by Yang Wu (66682)

    Published 2025
    “…Our methods are implemented in Python and are freely available from GitHub (<a href="https://github.com/queryang/PASO" target="_blank">https://github.com/queryang/PASO</a>).…”
  3. 263

    PTPC v1.0 Numerical Baseline: Stable Multi-Bounce Cosmology Simulation by David Lewis Stewart Parry (22188211)

    Published 2025
    “…PTPC v1.0 Numerical Baseline: Stable Multi-Bounce Cosmology Simulation This release provides the complete, reproducible numerical implementation of the Parry Tensional Phase Collapse (PTPC) model — the dynamic core of the Universal Heartbeat Theory (UHT/PTPC). …”
  4. 264

    Table 3_Novel deep learning-based prediction of HER2 expression in breast cancer using multimodal MRI, nomogram, and decision curve analysis.docx by Shi Qiu (425335)

    Published 2025
    “…Nomogram construction, ROC analysis, and DCA evaluation were performed to assess model performance. Statistical analyses were conducted using Python and R, with significance set at p < 0.05.…”
  5. 265

    Table 2_Novel deep learning-based prediction of HER2 expression in breast cancer using multimodal MRI, nomogram, and decision curve analysis.docx by Shi Qiu (425335)

    Published 2025
    “…Nomogram construction, ROC analysis, and DCA evaluation were performed to assess model performance. Statistical analyses were conducted using Python and R, with significance set at p < 0.05.…”
  6. 266

    Table 1_Novel deep learning-based prediction of HER2 expression in breast cancer using multimodal MRI, nomogram, and decision curve analysis.docx by Shi Qiu (425335)

    Published 2025
    “…Nomogram construction, ROC analysis, and DCA evaluation were performed to assess model performance. Statistical analyses were conducted using Python and R, with significance set at p < 0.05.…”
  7. 267

    Data Sheet 1_Novel deep learning-based prediction of HER2 expression in breast cancer using multimodal MRI, nomogram, and decision curve analysis.docx by Shi Qiu (425335)

    Published 2025
    “…Nomogram construction, ROC analysis, and DCA evaluation were performed to assess model performance. Statistical analyses were conducted using Python and R, with significance set at p < 0.05.…”
  8. 268

    Fast, FAIR, and Scalable: Managing Big Data in HPC with Zarr by Alfonso Ladino (21447002)

    Published 2025
    “…</p><p dir="ltr">In this work, we apply the scientific datacube model to the transformation of large-scale radar datasets from Colombia and the U.S. …”
  9. 269

    Summary of Tourism Dataset. by Jing Zhang (23775)

    Published 2025
    “…The implementation uses Python language on a tourism dataset comprising necessary attributes like visitor numbers, days, spending patterns, employment, international tourism samples over a specific region, and a diverse age group analyzed over a year. …”
  10. 270

    Segment-wise Spending Analysis. by Jing Zhang (23775)

    Published 2025
    “…The implementation uses Python language on a tourism dataset comprising necessary attributes like visitor numbers, days, spending patterns, employment, international tourism samples over a specific region, and a diverse age group analyzed over a year. …”
  11. 271

    Hyperparameter Parameter Setting. by Jing Zhang (23775)

    Published 2025
    “…The implementation uses Python language on a tourism dataset comprising necessary attributes like visitor numbers, days, spending patterns, employment, international tourism samples over a specific region, and a diverse age group analyzed over a year. …”
  12. 272

    Marketing Campaign Analysis. by Jing Zhang (23775)

    Published 2025
    “…The implementation uses Python language on a tourism dataset comprising necessary attributes like visitor numbers, days, spending patterns, employment, international tourism samples over a specific region, and a diverse age group analyzed over a year. …”
  13. 273

    Visitor Segmentation Validation Accuracy. by Jing Zhang (23775)

    Published 2025
    “…The implementation uses Python language on a tourism dataset comprising necessary attributes like visitor numbers, days, spending patterns, employment, international tourism samples over a specific region, and a diverse age group analyzed over a year. …”
  14. 274

    Integration of VAE and RNN Architecture. by Jing Zhang (23775)

    Published 2025
    “…The implementation uses Python language on a tourism dataset comprising necessary attributes like visitor numbers, days, spending patterns, employment, international tourism samples over a specific region, and a diverse age group analyzed over a year. …”
  15. 275

    Folder with all data and algorithms by Jorge Servert Lerdo de Tejada (22290001)

    Published 2025
    “…In this study, we present an open-source, Python-based computational framework that unifies photon transport modeling, probe geometry optimization, and photothermal safety assessment into a single workflow. …”
  16. 276

    CNG-ARCO-RADAR.pdf by Alfonso Ladino (21447002)

    Published 2025
    “…This approach uses a suite of Python libraries, including Xarray (Xarray-Datatree), Xradar, and Zarr, to implement a hierarchical tree-like data model. …”
  17. 277

    Soulware-Lite by Abhiram Gnyanijaya (21572942)

    Published 2025
    “…It supports OpenAI GPT-4, Anthropic Claude, Google Gemini, Meta LLaMA, and other open-source models.</p><p><br></p><p dir="ltr">Soulware-Lite is the first live implementation of a cognitive conscience layer, born from architectural failures in AI output hallucination and anchored by integrity principles like MAP/ARP and RDIP. …”
  18. 278

    Gene Editing using Transformer Architecture by Rishabh Garg (5261744)

    Published 2025
    “…., the H-Bot sequence), it facilitates on-screen gene editing, enabling targeted mutations or the insertion of desired genes. Implementation requires Python and deep learning frameworks like TensorFlow or PyTorch, with optional use of Biopython for genetic sequence handling. …”
  19. 279

    3D PD-Controlled Nanorobot Swarm Simulation for Targeted Cancer and BBB Therapy by Umar Tabbsum (22058780)

    Published 2025
    “…Cancer-targeting nanorobots converge rapidly, while BBB-targeting nanorobots follow more complex paths due to navigation constraints.</p><p dir="ltr">Implemented in Python (NumPy, Matplotlib, 3D visualization), the framework is fully annotated and reproducible. …”
  20. 280

    Globus Compute: Federated FaaS for Integrated Research Solutions by eRNZ Admin (6438486)

    Published 2025
    “…</p><p dir="ltr">Globus Compute [2] is a Function-as-a-Service platform designed to provide a scalable, secure, and simple interface to HPC resources. Globus Compute implements a federated model via which users may deploy endpoints on arbitrary remote computers, from the edge to high performance computing (HPC) cluster, and they may then invoke Python functions on those endpoints via a reliable cloud-hosted service. …”