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Polygenic risk modeling of tumor stage and survival in bladder cancer
Mauro Nascimben
,
Lia Rimondini
,
Davide Corà
, Manolo Venturin
Dipartimento di Scienze della Salute
Dipartimento di Medicina Traslazionale
Risultato della ricerca
:
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Ordina per
Peso
Alfabetico
Keyphrases
Analysis pipeline
33%
Approximation Parameters
16%
Approximation Techniques
16%
Bladder Cancer
100%
Cancer Prognosis
16%
Cancer Stage
16%
Cancer-specific Survival
16%
Class Prediction
16%
Clinical Decision Support
16%
Complete Data
33%
Complexity Features
16%
Cystoscopy
16%
Data Discretization
16%
Data Embedding
66%
Data Preprocessing
16%
Dimensionality Reduction
16%
Disease Outcome
16%
Disease Progression
16%
Gene Expression Data
50%
Gene Signature
16%
Literature Trends
16%
Machine Learning
16%
Machine Learning Experiments
16%
Machine Learning Techniques
33%
Manifold Approximation
100%
Manifold Projection
100%
Model Complex
16%
New Patients
33%
Nonlinear Dimensionality Reduction
16%
Number of Parameters
16%
Numerical Experiments
16%
Numerical Methods
16%
Oncology Patients
16%
Outcome Modeling
16%
Parameter Influence
16%
Parameter Space
16%
Partial Information
50%
Pathological Pattern
16%
Patient Condition
33%
Patient Prognosis
16%
Patients at Risk
16%
Polygenic Risk
100%
Predictive Ability
16%
Prognostic Biomarker
16%
Prognostic Maps
16%
Projection Method
16%
Projection Value
16%
Rapid Monitoring
16%
Relevance Analysis
16%
Relevant Genes
16%
Risk Modeling
100%
Statistical Techniques
16%
Survival Outcomes
16%
Survival Rate
16%
T-distributed Stochastic Neighbor Embedding (t-SNE)
33%
Tree Ensembles
16%
Tumor Outcome
16%
Tumor Stage
100%
Tumor Survival
100%
Uniform Data Set
16%
Well-defined
16%
Computer Science
Approximation (Algorithm)
100%
Class Prediction
16%
Data Discretization
16%
Data Preprocessing
16%
Dimensionality Reduction
33%
Discretization
16%
Disease Progression
16%
Embedding Data
66%
Experimental Result
16%
Gene Expression Data
50%
Learning System
66%
Machine Learning
66%
Mathematical Method
16%
Parameter Space
16%
Recent Literature
16%
Statistical Technique
16%
Medicine and Dentistry
Biological Marker
50%
Bladder Cancer
100%
Cancer Prognosis
25%
Cancer Staging
100%
Cancer Survival
25%
Cystoscopy
25%
Disease Exacerbation
25%
Diseases
25%
Gene Expression
75%
Gene Expression Profiling
25%
Malignant Neoplasm
25%
Neoplasm
25%
Survival Rate
25%
Biochemistry, Genetics and Molecular Biology
Cancer Staging
100%
Cancer Survival
33%
Dimensionality Reduction
66%
Gene Expression Data
100%
Gene Expression Profiling
33%
Survival Rate
33%
Immunology and Microbiology
Cancer Staging
100%
Cancer Survival
33%
Gene Expression
100%
Gene Expression Assay
33%
Survival Rate
33%
Neuroscience
Gene Expression
100%