Results for model hyperparameter values. by Hao Yang (328526)

“…The model is developed and validated using data from 159 debris flow-prone gullies, integrating deep convolutional, recurrent, and attention-based architectures, with hyperparameters autonomously optimized by IKOA. …”

Flow chart of this study. by Hao Yang (328526)

“…The model is developed and validated using data from 159 debris flow-prone gullies, integrating deep convolutional, recurrent, and attention-based architectures, with hyperparameters autonomously optimized by IKOA. …”

Stability analysis of each model. by Hao Yang (328526)

“…The model is developed and validated using data from 159 debris flow-prone gullies, integrating deep convolutional, recurrent, and attention-based architectures, with hyperparameters autonomously optimized by IKOA. …”

Robustness Analysis of each model. by Hao Yang (328526)

“…The model is developed and validated using data from 159 debris flow-prone gullies, integrating deep convolutional, recurrent, and attention-based architectures, with hyperparameters autonomously optimized by IKOA. …”

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

“…To overcome these shortcomings, this paper cites an improved SSA search algorithm that incorporates the ingestion strategy of the FA algorithm to increase the diversity of solutions and global search capability, the Firefly Algorithm-based Sparrow Search Optimization Algorithm (FA-SSA algorithm) is introduced. …”

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

“…To overcome these shortcomings, this paper cites an improved SSA search algorithm that incorporates the ingestion strategy of the FA algorithm to increase the diversity of solutions and global search capability, the Firefly Algorithm-based Sparrow Search Optimization Algorithm (FA-SSA algorithm) is introduced. …”

Error of models. by Qinghua Li (398885)

“…To overcome these shortcomings, this paper cites an improved SSA search algorithm that incorporates the ingestion strategy of the FA algorithm to increase the diversity of solutions and global search capability, the Firefly Algorithm-based Sparrow Search Optimization Algorithm (FA-SSA algorithm) is introduced. …”

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

“…To overcome these shortcomings, this paper cites an improved SSA search algorithm that incorporates the ingestion strategy of the FA algorithm to increase the diversity of solutions and global search capability, the Firefly Algorithm-based Sparrow Search Optimization Algorithm (FA-SSA algorithm) is introduced. …”

Table_1_One-Time Optimization of Advanced T Cell Culture Media Using a Machine Learning Pipeline.DOCX by Paul Grzesik (11136582)

“…When optimizing culture media for primary cells used in cell and gene therapy, traditional DoE approaches that depend on interpretable models will not always provide reliable predictions due to high donor variability. …”

Data_Sheet_1_Selection of a Real-Time PCR Housekeeping Gene Panel in Human Endothelial Colony Forming Cells for Cellular Senescence Studies.pdf by Kiran J. McLoughlin (6442688)

Table_1_Selection of a Real-Time PCR Housekeeping Gene Panel in Human Endothelial Colony Forming Cells for Cellular Senescence Studies.pdf by Kiran J. McLoughlin (6442688)

Table_2_Selection of a Real-Time PCR Housekeeping Gene Panel in Human Endothelial Colony Forming Cells for Cellular Senescence Studies.xlsx by Kiran J. McLoughlin (6442688)

Table_1_Machine learning models for assessing risk factors affecting health care costs: 12-month exercise-based cardiac rehabilitation.DOCX by Arto J. Hautala (3072576)

“…Since machine learning (ML) applications are rapidly giving new opportunities to assist health care professionals’ work, we used selected ML tools to assess the predictive value of defined risk factors for health care costs during 12-month ECR in patients with CAD.</p>Methods<p>The data for analysis was available from a total of 71 patients referred to Oulu University Hospital, Finland, due to an acute coronary syndrome (ACS) event (75% men, age 61 ± 12 years, BMI 27 ± 4 kg/m2, ejection fraction 62 ± 8, 89% have beta-blocker medication). …”

Data_Sheet_1_Hierarchical multi-class Alzheimer’s disease diagnostic framework using imaging and clinical features.docx by Yao Qin (385509)

DataSheet1_Quantum-assisted fragment-based automated structure generator (QFASG) for small molecule design: an in vitro study.docx by Sergei Evteev (18294157)

Supplementary Material for: The Therapeutic Evaluation of Steroids in IgA Nephropathy Global (TESTING) Study: Trial Design and Baseline Characteristics by Wong M.G. (11640685)

“…The mean age of randomized participants was 38, 39% were female, mean eGFR at randomization was 62.7 mL/min/1.73 m², and mean 24-h urine protein 2.54 g. The primary endpoint is a composite of 40% eGFR decline from baseline or kidney failure (dialysis, transplantation, or death due to kidney disease), and participants will be followed until the primary outcome has been observed in at least 160 randomized participants. …”

Image1_Adverse events related to neuromuscular blocking agents: a disproportionality analysis of the FDA adverse event reporting system.pdf by Liangxia Li (17664248)

“…A positive signal was generated when both algorithms show an association between the target drug and the AE.…”

Table1_Adverse events related to neuromuscular blocking agents: a disproportionality analysis of the FDA adverse event reporting system.xlsx by Liangxia Li (17664248)

“…A positive signal was generated when both algorithms show an association between the target drug and the AE.…”