The flowchart of the MAs selection process. by Samer Mheissen (8748501)

Primary characteristics and categories of the 31 studies. by Jiaxin Li (441199)

Features selected by optimization algorithms. by Afnan M. Alhassan (18349378)

“…Consequently, the prediction of BrC depends critically on the quick and precise processing of imaging data. The primary reason deep learning models are used in breast cancer detection is that they can produce findings more quickly and accurately than current machine learning-based techniques. …”

MLP vs classification algorithms. by Mohd Mustaqeem (19106494)

“…We propose SPAM-XAI, a hybrid model integrating novel sampling, feature selection, and eXplainable-AI (XAI) algorithms to address these challenges. …”

Construction process of RF. by Xini Fang (20861990)

“…Following this, the FCM clustering algorithm is utilized for pre-processing sample data to improve the efficiency and accuracy of data classification. …”

Primary characteristics and details of the 31 studies (Table 2 was uploaded as an additional file). by Jiaxin Li (441199)

Hybrid feature selection algorithm of CSCO-ROA. by Afnan M. Alhassan (18349378)

“…Consequently, the prediction of BrC depends critically on the quick and precise processing of imaging data. The primary reason deep learning models are used in breast cancer detection is that they can produce findings more quickly and accurately than current machine learning-based techniques. …”

Excel file with primary data used to assemble figures. by Ankit Srivastava (742990)

Schematic representation of univariate ensemble-based feature selection. by Nanavath Kiran Singh Nayak (22184565)

Subjects:

SLR-Resource Allocation in Business Processes: Selected studies and data extraction by Luise Pufahl (17695929)

Trajectory mode selection. by Anees ul Husnain (18017648)

Total primary energy demand by fuel in China. by Da Lian (18880882)

Pre-processing steps. by Yubraj Gupta (7465394)

Random forest model performs better than support vector machine algorithms and when it primarily uses spontaneous photopic ERG of 60-s duration in humans. by Ramsés Noguez Imm (6658637)

Weights of sample data. by Yixuan Lu (9987980)

Illustration of the cell detection process. by Adam L. Tyson (10892822)

Data_Sheet_1_Bayesian Modeling Immune Reconstitution Apply to CD34+ Selected Stem Cell Transplantation for Severe Combined Immunodeficiency.docx by Jean-Sebastien Diana (12087242)

Overview of the algorithmic approach and its place in the hypothesis generation toolkit. by Braden T. Tierney (8822813)

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. …”