Data_Sheet_1_Development and Validation of a Deep Learning Algorithm to Automatic Detection of Pituitary Microadenoma From MRI.docx by Qingling Li (1444981)

Image_4_Development and Validation of a Deep Learning Algorithm to Automatic Detection of Pituitary Microadenoma From MRI.TIF by Qingling Li (1444981)

Image_1_Development and Validation of a Deep Learning Algorithm to Automatic Detection of Pituitary Microadenoma From MRI.TIF by Qingling Li (1444981)

Image_7_Development and Validation of a Deep Learning Algorithm to Automatic Detection of Pituitary Microadenoma From MRI.TIF by Qingling Li (1444981)

Image_3_Development and Validation of a Deep Learning Algorithm to Automatic Detection of Pituitary Microadenoma From MRI.TIF by Qingling Li (1444981)

Image_2_Development and Validation of a Deep Learning Algorithm to Automatic Detection of Pituitary Microadenoma From MRI.TIF by Qingling Li (1444981)

Image_5_Development and Validation of a Deep Learning Algorithm to Automatic Detection of Pituitary Microadenoma From MRI.TIF by Qingling Li (1444981)

Image_6_Development and Validation of a Deep Learning Algorithm to Automatic Detection of Pituitary Microadenoma From MRI.TIF by Qingling Li (1444981)

The Venn diagram of the four different algorithms (Among the 3054 signal combinations, the ROR method identified 671 related signals, the PRR method identified 740, the MGPS method... by Gang Hao (134522)

MLP vs classification algorithms. by Mohd Mustaqeem (19106494)

“…Software defects are the primary concern, and software defect prediction (SDP) plays a crucial role in detecting faulty modules early and planning effective testing to reduce maintenance costs. …”

Evaluation of imputation methods through differential expression analysis on H1-DEC dataset. by Yuqing Qian (15323071)

Related studies on IDS using deep learning. by Arshad Hashmi (13835488)

“…<div><p>Due to the recent advances in the Internet and communication technologies, network systems and data have evolved rapidly. The emergence of new attacks jeopardizes network security and make it really challenging to detect intrusions. …”

The architecture of the BI-LSTM model. by Arshad Hashmi (13835488)

“…<div><p>Due to the recent advances in the Internet and communication technologies, network systems and data have evolved rapidly. The emergence of new attacks jeopardizes network security and make it really challenging to detect intrusions. …”

Comparison of accuracy and DR on UNSW-NB15. by Arshad Hashmi (13835488)

“…<div><p>Due to the recent advances in the Internet and communication technologies, network systems and data have evolved rapidly. The emergence of new attacks jeopardizes network security and make it really challenging to detect intrusions. …”

Comparison of DR and FPR of UNSW-NB15. by Arshad Hashmi (13835488)

“…<div><p>Due to the recent advances in the Internet and communication technologies, network systems and data have evolved rapidly. The emergence of new attacks jeopardizes network security and make it really challenging to detect intrusions. …”

Data_Sheet_1_Development of a deep learning model for automated detection of calcium pyrophosphate deposition in hand radiographs.docx by Thomas Hügle (177824)

Trace, Machine Learning of Signal Images for Trace-Sensitive Mass Spectrometry: A Case Study from Single-Cell Metabolomics by Zhichao Liu (191718)

“…However, extraction of trace-abundance signals from complex data sets (<i>m</i>/<i>z</i> value, separation time, signal abundance) that result from ultrasensitive studies requires improved data processing algorithms. …”

Trace, Machine Learning of Signal Images for Trace-Sensitive Mass Spectrometry: A Case Study from Single-Cell Metabolomics by Zhichao Liu (191718)

“…However, extraction of trace-abundance signals from complex data sets (<i>m</i>/<i>z</i> value, separation time, signal abundance) that result from ultrasensitive studies requires improved data processing algorithms. …”

Risperidone.zip. by Gang Hao (134522)

“…Signal detection was performed using the reporting odds ratio, proportional reporting ratio, Bayesian confidence propagation neural network, and multi-item gamma Poisson shrinker algorithms.…”

Basic Information on AE reports for Risperidone. by Gang Hao (134522)

“…Signal detection was performed using the reporting odds ratio, proportional reporting ratio, Bayesian confidence propagation neural network, and multi-item gamma Poisson shrinker algorithms.…”