ReviewNPJ precision oncology2024
Radiology and multi-scale data integration for precision oncology.
Review in NPJ precision oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
20 citing papers in PubMed.
- Multi-omics-driven precision medicine.iMeta · 2026Review
- Handling missing data: AI approach for survival prediction in lung cancer despite missing data.NPJ digital medicine · 2026Article
- Handling missing modalities in multimodal survival prediction for non-small cell lung cancer.NPJ digital medicine · 2026Article
- Radiomic signatures associated with longitudinal TNM downstaging for prognostic stratification in breast cancer.Insights into imaging · 2026Article
- Reply to Letter to the Editor: Deep learning for accurate tumour volume measurement and prediction of therapy response in paediatric osteosarcoma.European radiology · 2026Article
- From Artificial Intelligence to Robotics: How to Navigate Technological Innovation in Radiology With the Gartner Hype Cycle.Academic radiology · 2026Review
- Radiomics and deep learning in upper tract urothelial carcinoma: advancing preoperative risk stratification and clinical decision-making.Frontiers in oncology · 2026Review
- Immune checkpoint inhibitor therapy for gastric cancer: current status, therapeutic challenges, and future prospects.Frontiers in immunology · 2026Review
- Structured proxy features for multimodal NSCLC survival prediction from pretreatment CT.Frontiers in artificial intelligence · 2026Article
- Applications of artificial intelligence in non-small cell lung cancer: from precision diagnosis to personalized prognosis and therapy.Journal of translational medicine · 2025Review
- HONeYBEE: enabling scalable multimodal AI in oncology through foundation model-driven embeddings.NPJ digital medicine · 2025Article
- A feasibility study of [18F] FDG PET/CT radiomics in predicting high-risk cytogenetic abnormalities in multiple myeloma.EJNMMI research · 2025Article
- Intervention on Modifiable Lifestyle and Physiological Factors via Variational Autoencoder Reveals Changes in Functional Connectivity-Mediated Risk for Alzheimer's Disease.medRxiv : the preprint server for health sciences · 2025Article
- Bayesian Graphical Models for Multiscale Inference in Medical Image-Based Joint Degeneration Analysis.Diagnostics (Basel, Switzerland) · 2025Review
- Precision Neuro-Oncology in Glioblastoma: AI-Guided CRISPR Editing and Real-Time Multi-Omics for Genomic Brain Surgery.International journal of molecular sciences · 2025Review
- Multi-omics perspectives for gastrointestinal malignancy: A systematic review.World journal of gastrointestinal surgery · 2025Article
- Challenges in AI-driven Biomedical Multimodal Data Fusion and Analysis.Genomics, proteomics & bioinformatics · 2025Review
- The need for evidence-based, outcome-focused medical imaging research for cancer management.Npj imaging · 2025Article
- A critical assessment of artificial intelligence in magnetic resonance imaging of cancer.Npj imaging · 2025Review
- Integrated multicenter deep learning system for prognostic prediction in bladder cancer.NPJ precision oncology · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In this Perspective paper we explore the potential of integrating radiological imaging with other data types, a critical yet underdeveloped area in comparison to the fusion of other multi-omic data. Radiological images provide a comprehensive, three-dimensional view of cancer, capturing features that would be missed by biopsies or other data modalities. This paper explores the complexities and challenges of incorporating medical imaging into data integration models, in the context of precision oncology. We present the different categories of imaging-omics integration and discuss recent progress, highlighting the opportunities that arise from bringing together spatial data on different scales.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.