Several loop patterns found in binary code. حسب Alba Pedro-Zapater (8600382)

<i>Patient 1</i> GA-optimized model error. حسب Dmitrii Smirnov (8822324)

الموضوعات:

<i>Patient 8</i> GA-optimized model error. حسب Dmitrii Smirnov (8822324)

الموضوعات:

Optimal Drug-Target Docking Visualization. حسب Qijun Wo (12992781)

Algorithm verification. حسب Dmitrii Smirnov (8822324)

الموضوعات:

Genetic Algorithm (GA) and CAGE-based personalization block diagrams. حسب Dmitrii Smirnov (8822324)

الموضوعات:

Screening MMRG gene variables associated with UC based on the optimal machine learning model. حسب Li Li (14993)

Proposed Algorithm. حسب Hend Bayoumi (22693738)

"…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. …"

<i>Patient 2</i> CAGE-based model error. حسب Dmitrii Smirnov (8822324)

الموضوعات:

<i>Patient 9–11</i> RNA-seq based models error. حسب Dmitrii Smirnov (8822324)

الموضوعات:

Comparisons between ADAM and NADAM optimizers. حسب Hend Bayoumi (22693738)

"…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. …"

Comparison of presented algorithm precision to Bot et al. حسب Dmitrii Smirnov (8822324)

الموضوعات:

Model convergence to steady state. حسب Dmitrii Smirnov (8822324)

الموضوعات:

Key gene identification based on two machine learning algorithms. حسب Lijun Guo (605276)

The Pseudo-Code of the IRBMO Algorithm. حسب Chenyi Zhu (9383370)

"…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …"

Distributions of model parameters mirror differentially expressed ion channel genes. حسب Daniele Linaro (227790)

<i>Patient 8</i> GA output model. حسب Dmitrii Smirnov (8822324)

الموضوعات:

The flow chart of harmony search-based OED using a double nested loops. حسب Wei Zhang (405)

Table 1_A computational framework for optimizing mRNA vaccine delivery via AI-guided nanoparticle design and in silico gene expression profiling.pdf حسب Valentina Di Salvatore (6296114)

"…Parallelly, we trained a Random Forest regression model on simulated lipid nanoparticles formulations to predict immune activation values and embedded this model into a genetic algorithm to identify optimal lipid nanoparticles design parameters (size, charge, polyethylene glycol content, and targeting). …"

Presentation 1_A computational framework for optimizing mRNA vaccine delivery via AI-guided nanoparticle design and in silico gene expression profiling.pdf حسب Valentina Di Salvatore (6296114)

"…Parallelly, we trained a Random Forest regression model on simulated lipid nanoparticles formulations to predict immune activation values and embedded this model into a genetic algorithm to identify optimal lipid nanoparticles design parameters (size, charge, polyethylene glycol content, and targeting). …"