Data Sheet 1_Development of a novel artificial intelligence algorithm for interpreting fetal heart rate and uterine activity data in cardiotocography.docx حسب Rohit Pardasani (22253656)

"…The algorithm using deep learning and rule-based techniques was developed to identify segments of interest (accelerations, decelerations, and contractions). …"

Data Sheet 3_A prognostic model for highly aggressive prostate cancer using interpretable machine learning techniques.zip حسب Cong Peng (160287)

"…Feature selection was performed using the Boruta algorithm, and survival predictions were made using nine machine learning algorithms, including XGBoost, logistic regression (LR), support vector machine (SVM), random forest (RF), k-nearest neighbor (KNN), decision tree (DT), elastic network (Enet), multilayer perceptron (MLP) and lightGBM. …"

Data Sheet 2_A prognostic model for highly aggressive prostate cancer using interpretable machine learning techniques.zip حسب Cong Peng (160287)

"…Feature selection was performed using the Boruta algorithm, and survival predictions were made using nine machine learning algorithms, including XGBoost, logistic regression (LR), support vector machine (SVM), random forest (RF), k-nearest neighbor (KNN), decision tree (DT), elastic network (Enet), multilayer perceptron (MLP) and lightGBM. …"

Data Sheet 4_A prognostic model for highly aggressive prostate cancer using interpretable machine learning techniques.zip حسب Cong Peng (160287)

"…Feature selection was performed using the Boruta algorithm, and survival predictions were made using nine machine learning algorithms, including XGBoost, logistic regression (LR), support vector machine (SVM), random forest (RF), k-nearest neighbor (KNN), decision tree (DT), elastic network (Enet), multilayer perceptron (MLP) and lightGBM. …"

Data Sheet 6_A prognostic model for highly aggressive prostate cancer using interpretable machine learning techniques.docx حسب Cong Peng (160287)

"…Feature selection was performed using the Boruta algorithm, and survival predictions were made using nine machine learning algorithms, including XGBoost, logistic regression (LR), support vector machine (SVM), random forest (RF), k-nearest neighbor (KNN), decision tree (DT), elastic network (Enet), multilayer perceptron (MLP) and lightGBM. …"

Data Sheet 1_A prognostic model for highly aggressive prostate cancer using interpretable machine learning techniques.pdf حسب Cong Peng (160287)

"…Feature selection was performed using the Boruta algorithm, and survival predictions were made using nine machine learning algorithms, including XGBoost, logistic regression (LR), support vector machine (SVM), random forest (RF), k-nearest neighbor (KNN), decision tree (DT), elastic network (Enet), multilayer perceptron (MLP) and lightGBM. …"

Data Sheet 1_Identifying network state-based Parkinson’s disease subtypes using clustering and support vector machine models.pdf حسب Benedictor Alexander Nguchu (9984371)

"…</p>Methods<p>Here, we employ K-means and hierarchical clustering algorithms on data from the Parkinson’s Progression Markers Initiative (PPMI) to identify network-specific patterns that describe PD subtypes using the optimal number of brain features. …"

Triboelectric Sensors Based on Glycerol/PVA Hydrogel and Deep Learning Algorithms for Neck Movement Monitoring حسب Bingbing Qu (17603577)

"…By leveraging the convolutional neural network (CNN) and bidirectional long short-term memory (BiLSTM) algorithm, sensor data can be efficiently analyzed in both spatial and temporal dimensions, achieving a promising recognition accuracy of 97.14%. …"

Triboelectric Sensors Based on Glycerol/PVA Hydrogel and Deep Learning Algorithms for Neck Movement Monitoring حسب Bingbing Qu (17603577)

"…By leveraging the convolutional neural network (CNN) and bidirectional long short-term memory (BiLSTM) algorithm, sensor data can be efficiently analyzed in both spatial and temporal dimensions, achieving a promising recognition accuracy of 97.14%. …"

Triboelectric Sensors Based on Glycerol/PVA Hydrogel and Deep Learning Algorithms for Neck Movement Monitoring حسب Bingbing Qu (17603577)

"…By leveraging the convolutional neural network (CNN) and bidirectional long short-term memory (BiLSTM) algorithm, sensor data can be efficiently analyzed in both spatial and temporal dimensions, achieving a promising recognition accuracy of 97.14%. …"

Triboelectric Sensors Based on Glycerol/PVA Hydrogel and Deep Learning Algorithms for Neck Movement Monitoring حسب Bingbing Qu (17603577)

"…By leveraging the convolutional neural network (CNN) and bidirectional long short-term memory (BiLSTM) algorithm, sensor data can be efficiently analyzed in both spatial and temporal dimensions, achieving a promising recognition accuracy of 97.14%. …"

Data Sheet 1_A combined model of shoot phosphorus uptake based on sparse data and active learning algorithm.pdf حسب Tianli Wang (1438498)

Knowledge Graph validation using SHACL Shapes حسب Ángel Iglesias Préstamo (19745767)

Research data. حسب Dominique Vincent-Genod (20552594)

الموضوعات:

Comparison of Proposed Model using Unseen Data. حسب Saim Chishti (22272188)

"…Various models have successfully identified beta-thalassemia carriers using CBC data alone, but these models perform classification and prediction based on normalized data. …"

Comparison of proposed model using unseen data. حسب Saim Chishti (22272188)

"…Various models have successfully identified beta-thalassemia carriers using CBC data alone, but these models perform classification and prediction based on normalized data. …"

Genome-wide identification of candidate regions associated with birth weight in Lori-Bakhtiari sheep using Random Forest algorithm حسب Mohammad Hossein Moradi (11400671)

"…This study was conducted to identify genetic loci associated with birth weight in a meat-type sheep using a Random Forest (RF) algorithm applied to genomic data. …"

Data Sheet 2_Machine learning algorithm based on combined clinical indicators for the prediction of infertility and pregnancy loss.zip حسب Rui Zhang (13940)

"…The model for potential pregnancy loss was also developed using five machine learning algorithms and was based on 7 indicators. …"

Data Sheet 1_Machine learning algorithm based on combined clinical indicators for the prediction of infertility and pregnancy loss.docx حسب Rui Zhang (13940)

"…The model for potential pregnancy loss was also developed using five machine learning algorithms and was based on 7 indicators. …"

Solution results of different algorithms. حسب Meilin Zhu (688698)

"…Firstly, from the perspective of data-driven, it crawls the historical data of driving speed through Baidu map big data platform, and uses a BP neural network optimized by genetic algorithm to predict the driving speed of vehicles in different periods. …"