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

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

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

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

Friedman average rank sum test results. حسب Chenyi Zhu (9383370)

The baseline case–the model in the absence of sentinel plants. حسب Francesca A. Lovell-Read (14378253)

Proposed method approach. حسب Muhammad Usman Tariq (11022141)

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

LSTM model performance. حسب Muhammad Usman Tariq (11022141)

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

Descriptive statistics. حسب Muhammad Usman Tariq (11022141)

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

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

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

MLP Model performance. حسب Muhammad Usman Tariq (11022141)

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

RNN Model performance. حسب Muhammad Usman Tariq (11022141)

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

CNN Model performance. حسب Muhammad Usman Tariq (11022141)

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

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

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

<i>hi</i>PRS algorithm process flow. حسب Michela C. Massi (14599915)

"…From this dataset we can compute the MI between each interaction and the outcome and <b>(D)</b> obtain a ranked list (<i>I</i>_<i>δ</i>) based on this metric. …"

Steps in the extraction of 14 coordinates from the CT slices for the curved MPR. حسب Linus Woitke (22783534)

Design and implementation of the Multiple Criteria Decision Making (MCDM) algorithm for predicting the severity of COVID-19. حسب Jiaqing Luo (10975030)

"…P <0.05 was considered statistically significant. (B). The MCDM algorithm-Stage 2. Feature Ranking, this stage is the process of using the TOPSIS method to rank features. …"

Supplementary information for Efficient distributed edge computing for dependent delay-sensitive tasks in multi-operator multi-access networks حسب Alia Asheralieva (17562462)

"…We prove that the game has a perfect Bayesian equilibrium (PBE) yielding unique optimal values, and formulate new Bayesian reinforcement learning and Bayesian deep reinforcement learning algorithms enabling each PN to reach the PBE autonomously (without communicating with other PNs).…"

Data_Sheet_1_Prediction of Mental Health in Medical Workers During COVID-19 Based on Machine Learning.ZIP حسب Xiaofeng Wang (119575)

"…In this study, we propose a novel prediction model based on optimization algorithm and neural network, which can select and rank the most important factors that affect mental health of medical workers. …"

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... حسب Gaosen Zhang (539619)

"…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.…"