Data_Sheet_1_Early detection of sepsis using machine learning algorithms: a systematic review and network meta-analysis.pdf by Mikhail Ya Yadgarov (18543769)

Data used in this study. by Qinghua Li (398885)

“…To prevent issues such as overfitting or underfitting during model training, although common meta-heuristic optimisation algorithms can alleviate these problems to a certain extent, they still have some shortcomings. …”

DEM error verified by airborne data. by Qinghua Li (398885)

“…To prevent issues such as overfitting or underfitting during model training, although common meta-heuristic optimisation algorithms can alleviate these problems to a certain extent, they still have some shortcomings. …”

Error of ICESat-2 with respect to airborne data. by Qinghua Li (398885)

“…To prevent issues such as overfitting or underfitting during model training, although common meta-heuristic optimisation algorithms can alleviate these problems to a certain extent, they still have some shortcomings. …”

Data_Sheet_1_Measuring the impact of monoclonal antibody therapies.pdf by Ka Keat Lim (8915009)

Data_Sheet_1_Measuring the impact of monoclonal antibody therapies.pdf by Ka Keat Lim (8915009)

Datasheet1_Implantable cardioverter defibrillator for primary prevention in patients with non-ischemic cardiomyopathy in the era of novel therapeutic agents- meta-analysis.docx by Yotam Kolben (15787781)

“…The primary outcome included death from any cause. We did a meta-regression analysis to search for a single independent factor affecting mortality. …”

Proposed model tuned hyperparameters. by Subathra Gunasekaran (19492680)

“…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …”

The workflow of the proposed model. by Subathra Gunasekaran (19492680)

“…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …”

ResNeXt101 training and results. by Subathra Gunasekaran (19492680)

“…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …”

Proposed model specificity and DSC outcomes. by Subathra Gunasekaran (19492680)

“…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …”

Accuracy comparison of proposed and other models. by Subathra Gunasekaran (19492680)

“…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …”

Architecture of ConvNet. by Subathra Gunasekaran (19492680)

“…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …”

Comparison of state-of-the-art method. by Subathra Gunasekaran (19492680)

“…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …”

Proposed model sensitivity outcome. by Subathra Gunasekaran (19492680)

“…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …”

Proposed ResNeXt101 operational flow. by Subathra Gunasekaran (19492680)

“…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …”

Transect in parts of California. by Qinghua Li (398885)

“…To prevent issues such as overfitting or underfitting during model training, although common meta-heuristic optimisation algorithms can alleviate these problems to a certain extent, they still have some shortcomings. …”

Workflow of COP30DEM deviation correction model. by Qinghua Li (398885)

“…To prevent issues such as overfitting or underfitting during model training, although common meta-heuristic optimisation algorithms can alleviate these problems to a certain extent, they still have some shortcomings. …”

Error of models. by Qinghua Li (398885)

“…To prevent issues such as overfitting or underfitting during model training, although common meta-heuristic optimisation algorithms can alleviate these problems to a certain extent, they still have some shortcomings. …”

Prediction results of different models. by Qinghua Li (398885)

“…To prevent issues such as overfitting or underfitting during model training, although common meta-heuristic optimisation algorithms can alleviate these problems to a certain extent, they still have some shortcomings. …”