Path2Surv: Pathway/gene set-based survival analysis using multiple kernel learning

Mathematics

• Pathway 100%
• Survival Analysis 93%
• Gene 81%
• Learning 75%
• kernel 56%
• Random Forest 48%
• Support Vector Machine 41%
• Cancer 34%
• Gene Expression Profile 27%
• Predictive Model 22%
• Gene Expression 21%
• Learning Algorithm 19%
• Genomics 19%
• Machine Learning 18%
• Training 17%
• Integrate 17%
• Performance 9%
• Subset 9%
• Model 5%

Medicine & Life Sciences

• Survival Analysis 81%
• Learning 61%
• Survival 46%
• Support Vector Machine 40%
• Forests 39%
• Genes 33%
• Machine Learning 18%
• Transcriptome 15%
• Datasets 13%
• Neoplasms 10%
• Gene Expression 10%

Engineering & Materials Science

• Genes 79%
• Gene expression 45%
• Random forests 43%
• Support vector machines 33%
• Learning algorithms 17%
• Machine learning 15%
• Set theory 13%