Protocol for Classification Single-Cell PBMC Types from Pathological Samples Using Supervised Machine Learning

Keyphrases

• Peripheral Blood Mononuclear Cells 100%
• Supervised Machine Learning 100%
• Single-cell Transcriptomics 83%
• Classification Model 16%
• Unsupervised Clustering 16%
• Cell-to-cell 16%
• Transcriptomic Data 16%
• Immune System 16%
• Vaccine Development 16%
• Gene Expression Pattern 16%
• Manual Correction 16%
• Biological Samples 16%
• Data Preprocessing 16%
• Five Cells 16%
• Unsupervised Method 16%
• Building Classification 16%
• Disease Classification 16%
• Infectious Diseases 16%
• Therapeutic Intervention 16%
• Disease Development 16%
• Supervised Methods 16%
• Infectious Disease Vaccine 16%
• Genomic Technologies 16%
• Cancer Development 16%
• Single-cell Analysis 16%
• Blood Cells 16%
• Virus-associated Cancer 16%
• Pathological State 16%

Biochemistry, Genetics and Molecular Biology

• Peripheral Blood Mononuclear Cell 100%
• Supervised Machine Learning 100%
• Transcriptomics 83%
• Gene Expression 16%
• Hemocyte 16%
• Single-Cell Analysis 16%