Back to search

Article

Explainable Bayesian Artificial Intelligence for Precision Oncology: A Multimodal Framework for Personalized Cancer Prognosis

2026-06-23

Abstract excerpt

<title>Abstract</title> <p>Precision oncology strives to enhance cancer prediction and treatment decision-making by integrating multiple patient-specific data sources. Due to data heterogeneity, high complexity, and predictive modeling uncertainty, combining clinical, genetic, and imaging data is difficult. New Hierarchical Bayesian Multimodal Attention Fusion Network (HBMAF-Net) for customized cancer prediction...

Topics

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

Identifiers and source

Literature Corpus work
ae9a2594-47cf-5b79-8e3c-5ebf051a9a29
DOI
10.21203/rs.3.rs-10115658/v1
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
Explainable Bayesian Artificial Intelligence for Precision Oncology: A Multimodal Framework for Personalized Cancer PrognosisDOI 10.21203/rs.3.rs-10115658/v1
Select a neighboring publication to make it the new centre.