Showing 1 - 18 results of 18 for search '(( binary data codon optimization algorithm ) OR ( primary case guided optimization algorithm ))', query time: 0.41s Refine Results
  1. 1

    Models’ performance without optimization. by Muhammad Usman Tariq (11022141)

    Published 2024
    “…The findings indicate that the selected deep learning algorithms were proficient in forecasting COVID-19 cases, although their efficacy varied across different models. …”
  2. 2

    RNN performance comparison with/out optimization. by Muhammad Usman Tariq (11022141)

    Published 2024
    “…The findings indicate that the selected deep learning algorithms were proficient in forecasting COVID-19 cases, although their efficacy varied across different models. …”
  3. 3

    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. …”
  4. 4

    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. …”
  5. 5

    Proposed method approach. by Muhammad Usman Tariq (11022141)

    Published 2024
    “…The findings indicate that the selected deep learning algorithms were proficient in forecasting COVID-19 cases, although their efficacy varied across different models. …”
  6. 6

    LSTM model performance. by Muhammad Usman Tariq (11022141)

    Published 2024
    “…The findings indicate that the selected deep learning algorithms were proficient in forecasting COVID-19 cases, although their efficacy varied across different models. …”
  7. 7

    Descriptive statistics. by Muhammad Usman Tariq (11022141)

    Published 2024
    “…The findings indicate that the selected deep learning algorithms were proficient in forecasting COVID-19 cases, although their efficacy varied across different models. …”
  8. 8

    CNN-LSTM Model performance. by Muhammad Usman Tariq (11022141)

    Published 2024
    “…The findings indicate that the selected deep learning algorithms were proficient in forecasting COVID-19 cases, although their efficacy varied across different models. …”
  9. 9

    MLP Model performance. by Muhammad Usman Tariq (11022141)

    Published 2024
    “…The findings indicate that the selected deep learning algorithms were proficient in forecasting COVID-19 cases, although their efficacy varied across different models. …”
  10. 10

    RNN Model performance. by Muhammad Usman Tariq (11022141)

    Published 2024
    “…The findings indicate that the selected deep learning algorithms were proficient in forecasting COVID-19 cases, although their efficacy varied across different models. …”
  11. 11

    CNN Model performance. by Muhammad Usman Tariq (11022141)

    Published 2024
    “…The findings indicate that the selected deep learning algorithms were proficient in forecasting COVID-19 cases, although their efficacy varied across different models. …”
  12. 12

    Bi-directional LSTM Model performance. by Muhammad Usman Tariq (11022141)

    Published 2024
    “…The findings indicate that the selected deep learning algorithms were proficient in forecasting COVID-19 cases, although their efficacy varied across different models. …”
  13. 13
  14. 14

    DataSheet_1_A machine learning model based on ultrasound image features to assess the risk of sentinel lymph node metastasis in breast cancer patients: Applications of scikit-learn... by Gaosen Zhang (539619)

    Published 2022
    “…The diagnostic performance of the XGBoost model was significantly higher than that of experienced radiologists in some cases (P<0.001). Using SHAP to visualize the interpretation of the ML model screen, it was found that the ultrasonic detection of suspicious lymph nodes, microcalcifications in the primary tumor, burrs on the edge of the primary tumor, and distortion of the tissue structure around the lesion contributed greatly to the diagnostic performance of the XGBoost model.…”
  15. 15

    Supplementary file 2_Machine learning enables early risk stratification of hymenopteran stings: evidence from a tropical multicenter cohort.xlsx by Feng Han (10919)

    Published 2025
    “…</p>Methods<p>We retrospectively analyzed 942 cases from a multicenter cohort in Hainan Province, China. …”
  16. 16

    Image 1_Machine learning enables early risk stratification of hymenopteran stings: evidence from a tropical multicenter cohort.png by Feng Han (10919)

    Published 2025
    “…</p>Methods<p>We retrospectively analyzed 942 cases from a multicenter cohort in Hainan Province, China. …”
  17. 17

    Supplementary file 1_Machine learning enables early risk stratification of hymenopteran stings: evidence from a tropical multicenter cohort.docx by Feng Han (10919)

    Published 2025
    “…</p>Methods<p>We retrospectively analyzed 942 cases from a multicenter cohort in Hainan Province, China. …”
  18. 18

    Image 2_Machine learning enables early risk stratification of hymenopteran stings: evidence from a tropical multicenter cohort.png by Feng Han (10919)

    Published 2025
    “…</p>Methods<p>We retrospectively analyzed 942 cases from a multicenter cohort in Hainan Province, China. …”