Gene Expression Data Based Deep Learning Model for Accurate Prediction of Drug-Induced Liver Injury in Advance حسب Chunlai Feng (2228515)

"…In addition, the previous machine learning algorithm support vector machine (SVM) was also used to construct another prediction model based on the same data sets, comparing the model performance with the optimal DL model. …"

Gene Expression Data Based Deep Learning Model for Accurate Prediction of Drug-Induced Liver Injury in Advance حسب Chunlai Feng (2228515)

"…In addition, the previous machine learning algorithm support vector machine (SVM) was also used to construct another prediction model based on the same data sets, comparing the model performance with the optimal DL model. …"

Gene Expression Data Based Deep Learning Model for Accurate Prediction of Drug-Induced Liver Injury in Advance حسب Chunlai Feng (2228515)

"…In addition, the previous machine learning algorithm support vector machine (SVM) was also used to construct another prediction model based on the same data sets, comparing the model performance with the optimal DL model. …"

Gene Expression Data Based Deep Learning Model for Accurate Prediction of Drug-Induced Liver Injury in Advance حسب Chunlai Feng (2228515)

"…In addition, the previous machine learning algorithm support vector machine (SVM) was also used to construct another prediction model based on the same data sets, comparing the model performance with the optimal DL model. …"

Gene Expression Data Based Deep Learning Model for Accurate Prediction of Drug-Induced Liver Injury in Advance حسب Chunlai Feng (2228515)

"…In addition, the previous machine learning algorithm support vector machine (SVM) was also used to construct another prediction model based on the same data sets, comparing the model performance with the optimal DL model. …"

Gene Expression Data Based Deep Learning Model for Accurate Prediction of Drug-Induced Liver Injury in Advance حسب Chunlai Feng (2228515)

"…In addition, the previous machine learning algorithm support vector machine (SVM) was also used to construct another prediction model based on the same data sets, comparing the model performance with the optimal DL model. …"

Flow chart of Fuzzy Logic based control system. حسب Gourab Saha (8987405)

"…Finally, a fuzzy logic-based solar-powered irrigation system is used to monitor the water requirements of those crops and irrigate them according to their needs. …"

Flow chart of Average Value-based control system. حسب Gourab Saha (8987405)

"…Finally, a fuzzy logic-based solar-powered irrigation system is used to monitor the water requirements of those crops and irrigate them according to their needs. …"

Time complexity. حسب Xiaotong Bai (19819284)

"…In particular, the wrapper algorithm is an improved Grey Wolf Optimization (IGWO) algorithm based on random disturbance factors, while the parameters are adjusted to vary randomly to make the population variations rich in diversity. …"

Datasets information. حسب Xiaotong Bai (19819284)

"…In particular, the wrapper algorithm is an improved Grey Wolf Optimization (IGWO) algorithm based on random disturbance factors, while the parameters are adjusted to vary randomly to make the population variations rich in diversity. …"

Parameter settings. حسب Xiaotong Bai (19819284)

"…In particular, the wrapper algorithm is an improved Grey Wolf Optimization (IGWO) algorithm based on random disturbance factors, while the parameters are adjusted to vary randomly to make the population variations rich in diversity. …"

Minimum Chi-Square value. حسب Xiaotong Bai (19819284)

"…In particular, the wrapper algorithm is an improved Grey Wolf Optimization (IGWO) algorithm based on random disturbance factors, while the parameters are adjusted to vary randomly to make the population variations rich in diversity. …"

Basic steps of ReliefF. حسب Xiaotong Bai (19819284)

"…In particular, the wrapper algorithm is an improved Grey Wolf Optimization (IGWO) algorithm based on random disturbance factors, while the parameters are adjusted to vary randomly to make the population variations rich in diversity. …"

Feature correspondence position selection. حسب Xiaotong Bai (19819284)

"…In particular, the wrapper algorithm is an improved Grey Wolf Optimization (IGWO) algorithm based on random disturbance factors, while the parameters are adjusted to vary randomly to make the population variations rich in diversity. …"

Codes and datasets for AAAI 2021 paper "Learning to Pre-train Graph Neural Networks" حسب Yuanfu LU (8644788)

Dual UHPLC-HRMS Metabolomics and Lipidomics and Automated Data Processing Workflow for Comprehensive High-Throughput Gut Phenotyping حسب P. Vangeenderhuysen (15854812)

"…To automate targeted processing, we optimized an R-based targeted peak extraction (TaPEx) algorithm relying on a database comprising retention time and mass-to-charge ratio (360 metabolites and 132 lipids), with batch-specific quality control curation. …"

High-Throughput Approach for Minimum Energy Pathway Search Using the Nudged Elastic Band Method with Efficient Data Handling and Parallel Computing حسب Heejune Park (11130657)

"…The NEB and TS steps may be performed at different levels of theory, allowing us to perform NEB calculations with either DFT or PM7, followed by TS optimizations at the DFT level. The final TS structures were compared with reference geometries from the data set, which were further optimized at the corresponding level of theory. …"

Data_Sheet_1_Modeling intracranial electrodes. A simulation platform for the evaluation of localization algorithms.pdf حسب Alejandro O. Blenkmann (13914651)

"…Our work aimed to model intracranial electrode arrays and simulate realistic implantation scenarios, thereby providing localization algorithms with new ways to evaluate and optimize their performance.…"

Integration of multiple models into RfaH sequence design leads to reduction of sequence bias and variance. حسب Lu Hong (399882)

Results for the Pattern Generation task. حسب Paolo Muratore (8331585)