Search alternatives:
guided optimization » based optimization (Expand Search), model optimization (Expand Search)
codon optimization » wolf optimization (Expand Search)
primary case » primary cause (Expand Search), primary care (Expand Search), primary causes (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
case guided » cag guided (Expand Search), change guided (Expand Search), image guided (Expand Search)
data codon » data code (Expand Search), data codes (Expand Search), data codings (Expand Search)
guided optimization » based optimization (Expand Search), model optimization (Expand Search)
codon optimization » wolf optimization (Expand Search)
primary case » primary cause (Expand Search), primary care (Expand Search), primary causes (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
case guided » cag guided (Expand Search), change guided (Expand Search), image guided (Expand Search)
data codon » data code (Expand Search), data codes (Expand Search), data codings (Expand Search)
-
1
Models’ performance without optimization.
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
RNN performance comparison with/out optimization.
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
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
Published 2025“…Moreover, we propose a structured algorithm that may help optimize the clinical implementation of CAR-T therapy in similar cases. …”
-
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
Published 2025“…Moreover, we propose a structured algorithm that may help optimize the clinical implementation of CAR-T therapy in similar cases. …”
-
5
Proposed method approach.
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
LSTM model performance.
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
Descriptive statistics.
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
CNN-LSTM Model performance.
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
MLP Model performance.
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
RNN Model performance.
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
CNN Model performance.
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
Bi-directional LSTM Model performance.
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
-
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...
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
Supplementary file 2_Machine learning enables early risk stratification of hymenopteran stings: evidence from a tropical multicenter cohort.xlsx
Published 2025“…</p>Methods<p>We retrospectively analyzed 942 cases from a multicenter cohort in Hainan Province, China. …”
-
16
Image 1_Machine learning enables early risk stratification of hymenopteran stings: evidence from a tropical multicenter cohort.png
Published 2025“…</p>Methods<p>We retrospectively analyzed 942 cases from a multicenter cohort in Hainan Province, China. …”
-
17
Supplementary file 1_Machine learning enables early risk stratification of hymenopteran stings: evidence from a tropical multicenter cohort.docx
Published 2025“…</p>Methods<p>We retrospectively analyzed 942 cases from a multicenter cohort in Hainan Province, China. …”
-
18
Image 2_Machine learning enables early risk stratification of hymenopteran stings: evidence from a tropical multicenter cohort.png
Published 2025“…</p>Methods<p>We retrospectively analyzed 942 cases from a multicenter cohort in Hainan Province, China. …”