Article

Selection-bias-aware survival learning from tissue to population scale: A stabilized IPW–Cox method with a differentiable etiologic- heterogeneity head, validated on multimodal colorectal cancer and on 59,057 NHANES adults

2026-06-23

Abstract excerpt

<title>Abstract</title> <p>Survival models built on biomarker assays, tumor tissue, or molecular subtypes are routinely fit only on the subset of a cohort in which the measurement was actually performed. When that availability depends on the variables that drive the outcome, the analyzable subset is a biased draw and the fitted model estimates a selected-stratum association rather than the population quantity of...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: b4ac651b-60b4-5030-b610-0758e9085dee
DOI: 10.21203/rs.3.rs-10116532/v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Selection-bias-aware survival learning from tissue to population scale: A stabilized IPW–Cox method with a differentiable etiologic- heterogeneity head, validated on multimodal colorectal cancer and on 59,057 NHANES adultsDOI 10.21203/rs.3.rs-10116532/v1Read

A Pan-Cancer Multi-Omic SuperLearner for Regulated Cell Death Survival TopologiesSemantic proximity Read

Pre-Transformer Models for Longevity Science and Deep Ageing Clocks: An Empirical AnalysisSemantic proximity Read

Experimental Design Dominates Model Architecture in Multi-Model Cancer Classification: A Translational Bioinformatics Analysis Across Small-n and Large-n RegimesSemantic proximity Read

An explainable transformer model learning from entire treatment timelines for pan-cancer risk profiling across healthcare systemsSemantic proximity Read

A software package for simple and rigorous survival machine learning analysis in biomedical researchSemantic proximity Read

Network regularized Accelerated Failure Time Models for Robust Biomarker IdentificationSemantic proximity Read

Equitable Health Intelligence: An Open Benchmark of Multi-Population Machine Learning for Omics-Based Cancer PrognosisSemantic proximity Read

Tabular Foundation Model for Breast Cancer Prognosis using Gene Expression DataSemantic proximity Read

Machine Learning-Based Survival Time Prediction in Colorectal Cancer with Peritoneal Metastasis: A Multi-Institutional Registry-Based StudySemantic proximity Read

STRATA-PC: A Treatment-Aware, Outcome-Guided Deep Learning Framework for Prostate Cancer Risk StratificationSemantic proximity Read

Toward Foundation Models in Oncology: BCP-HyEnS: A Scalable Hybrid Ensemble Integrating Biomarkers and Explainability for Breast Cancer Diagnosis and TreatmentSemantic proximity Read

Restricted Multimodal Oncology AI: Role-Aware Evidence Organisation and Cross-Domain Transfer BoundariesSemantic proximity Read