A network-constrain Weibull AFT model for biomarkers discovery
We propose AFTNet, a novel network-constraint survival analysis method based on the Weibull accelerated failure time (AFT) model solved by a penalized likelihood approach for variable selection and estimation. When using the log-linear representation, the inference problem becomes a structured sparse regression problem for which we explicitly incorporate the correlation patterns among predictors using a double penalty that promotes both sparsity and grouping effect. Moreover, we establish the theoretical consistency for the AFTNet estimator and present an efficient iterative computational algorithm based on the proximal gradient descent method. Finally, we evaluate AFTNet performance both on synthetic and real data examples.
Code (0)
등록된 구현이 없습니다.
Tasks
Survival AnalysisVariable SelectionSimilar Papers 제목 키워드 기반
Graph-Based Biomarker Discovery and Interpretation for Alzheimer's Disease
Early diagnosis and discovery of therapeutic drug targets are crucial objectives for the effective management of Alzheimer's Disease (AD). Current approaches for AD diagnosis and treatment planning are based on radiologi…
DiagnosticDrug DiscoveryManagementBiomarker Discovery with Quantum Neural Networks: A Case-study in CTLA4-Activation Pathways
Biomarker discovery is a challenging task due to the massive search space. Quantum computing and quantum Artificial Intelligence (quantum AI) can be used to address the computational problem of biomarker discovery tasks.…
GRU-D-Weibull: A Novel Real-Time Individualized Endpoint Prediction
Accurate prediction models for individual-level endpoints and time-to-endpoints are crucial in clinical practice. In this study, we propose a novel approach, GRU-D-Weibull, which combines gated recurrent units with decay…
ManagementPredictionHow quantum computing can enhance biomarker discovery
Biomarkers play a central role in medicine's gradual progress towards proactive, personalized precision diagnostics and interventions. However, finding biomarkers that provide very early indicators of a change in health …
Time SeriesDeep-learning-based clustering of OCT images for biomarker discovery in age-related macular degeneration (Pinnacle study report 4)
Diseases are currently managed by grading systems, where patients are stratified by grading systems into stages that indicate patient risk and guide clinical management. However, these broad categories typically lack pro…
Contrastive Learning