Article

Bayesian Machine Learning for Precision Oncology: Integrating Clinical, Genomic, and Imaging Data for Personalized Cancer Prognosis

2026-06-24

Abstract excerpt

<title>Abstract</title> <p>Precision oncology aims to improve cancer prognosis and treatment decision-making by leveraging diverse patient-specific data sources. However, effectively integrating clinical, genomic, and imaging information remains challenging due to data heterogeneity, high dimensionality, and uncertainty in predictive modeling. This study proposes a novel Hierarchical Bayesian Multimodal Attention...

Topics

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

Identifiers and source

Literature Corpus work: bb0d24c6-9360-5bab-98d1-365368636453
DOI: 10.21203/rs.3.rs-10026817/v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Bayesian Machine Learning for Precision Oncology: Integrating Clinical, Genomic, and Imaging Data for Personalized Cancer PrognosisDOI 10.21203/rs.3.rs-10026817/v1Read

Explainable Bayesian Artificial Intelligence for Precision Oncology: A Multimodal Framework for Personalized Cancer PrognosisSemantic proximity Read

Deep learning-driven survival prediction in pan-cancer studies by integrating multimodal histology-genomic dataSemantic proximity Read

Hybrid Neural–Bayesian Belief Network Framework for Uncertainty-Aware Multimodal GBM PredictionSemantic proximity Read

Development of Biologically Interpretable Multimodal Deep Learning Model for Cancer Prognosis PredictionSemantic proximity Read

Explainable AI for Precision Oncology: A Task-Specific Approach Using Imaging, Multi-omics, and Clinical DataSemantic proximity Read

Multi-Modal Deep Learning Framework for Personalized Treatment Decision Support in Early-Stage Non-Small Cell Lung CancerSemantic proximity Read

MAFNet: A Multi-modal Deep Learning Framework for Comprehensive Tumor Microenvironment Analysis and Immunotherapy Response PredictionSemantic proximity Read

MRAN: A Reconstructive Attention Network for Handling Modality Sparsity in Multimodal Cancer Survival AnalysisSemantic proximity Read

Assessment of Emerging Pretraining Strategies in Interpretable Multimodal Deep Learning for Cancer PrognosticationSemantic proximity Read

Decoding pan-cancer treatment outcomes using multimodal real-world data and explainable artificial intelligenceSemantic proximity Read

PanoraOnc: A pan-cancer clinico-genomic AI model for transferable outcome predictionsSemantic proximity Read

Cooperative Modular Representation Learning for Lung Adenocarcinoma Survival Prediction from Transcriptomic and Clinical DataSemantic proximity Read