Showing 1 - 19 results of 19 for search '(( binary atp driven optimization algorithm ) OR ( primary care process optimization algorithm ))', query time: 0.39s Refine Results
  1. 1
  2. 2
  3. 3
  4. 4
  5. 5

    Data_Sheet_1_Accuracy of Deep Neural Network in Triaging Common Skin Diseases of Primary Care Attention.docx by Mara Giavina-Bianchi (11334102)

    Published 2021
    “…The triage process is usually conducted by primary care physicians; however, they may not be able to diagnose and assign the correct referral and level of priority for different dermatosis. …”
  6. 6
  7. 7
  8. 8
  9. 9
  10. 10
  11. 11
  12. 12
  13. 13
  14. 14
  15. 15

    Table 1_The future of critical care: AI-powered mortality prediction for acute variceal gastrointestinal bleeding and acute non-variceal gastrointestinal bleeding patients.docx by Zhou Liu (1506679)

    Published 2025
    “…Background<p>Acute upper gastrointestinal bleeding (AUGIB) is one of the most common critical diseases encountered in the intensive care unit (ICU), with a mortality rate ranging from 15 to 20%. …”
  16. 16

    Table 1_Durable response of primary cardiac lymphoma after autologous stem cell transplantation and sequential CAR-T therapy: a case report and literature review.docx by Ge Wang (56838)

    Published 2025
    “…Moreover, we propose a structured algorithm that may help optimize the clinical implementation of CAR-T therapy in similar cases. …”
  17. 17

    Data Sheet 1_Durable response of primary cardiac lymphoma after autologous stem cell transplantation and sequential CAR-T therapy: a case report and literature review.pdf by Ge Wang (56838)

    Published 2025
    “…Moreover, we propose a structured algorithm that may help optimize the clinical implementation of CAR-T therapy in similar cases. …”
  18. 18

    DATASET AI by Elena Stamate (18836305)

    Published 2025
    “…</p><p dir="ltr">The primary aim of this dataset is to enable the development and validation of machine learning models for:</p><ul><li>Early identification of STEMI patients at high risk of developing cardiogenic shock;</li><li>Clinical triage optimization and prioritization for urgent angiography;</li><li>Supporting time-sensitive decision-making in resource-limited or overcrowded emergency settings.…”
  19. 19

    Machine Learning-Ready Dataset for Cytotoxicity Prediction of Metal Oxide Nanoparticles by Soham Savarkar (21811825)

    Published 2025
    “…</p><p dir="ltr"><b>Applications and Model Compatibility:</b></p><p dir="ltr">The dataset is optimized for use in supervised learning workflows and has been tested with algorithms such as:</p><p dir="ltr">Gradient Boosting Machines (GBM),</p><p dir="ltr">Support Vector Machines (SVM-RBF),</p><p dir="ltr">Random Forests, and</p><p dir="ltr">Principal Component Analysis (PCA) for feature reduction.…”