ArticleProgress in biomedical engineering (Bristol, England)2023
Deep multimodal fusion of image and non-image data in disease diagnosis and prognosis: a review.
Article in Progress in biomedical engineering (Bristol, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
62 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Machine learning techniques for predicting neurodevelopmental impairments in premature infants: a systematic review.Frontiers in artificial intelligence · 2025Pooled it
- [Advances in deep learning multimodal fusion for early diagnosis of knee osteoarthritis].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2026Review
- Language-enhanced generative modeling for amyloid PET synthesis from MRI and blood biomarkers.iScience · 2026Article
- QGFace-LLaVA: Quality-Aware Controlled Fusion of Structured Side Information for Face Analysis Under Imperfect Metadata.Biomimetics (Basel, Switzerland) · 2026Article
- Hierarchical Multimodal Fusion of Multi-Sequence MRI and Clinical Metadata for the Classification of Rotator Cuff Tears.Journal of clinical medicine · 2026Article
- Bidirectional Perceptual Multimodal Interaction Network Based on Contrastive Learning for Breast Cancer pCR Prediction.Tomography (Ann Arbor, Mich.) · 2026Article
- Multimodal Wearable Biosensing Meets Multidomain AI: A Pathway to Decentralized Healthcare.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Multiple attention based deep multimodal fusion network for glaucoma and neurodegenerative disease diagnosis.Scientific reports · 2026Article
- Multimodal model integrating ultrasound and demographic data for the diagnosis of knee osteoarthritis.BMC medical imaging · 2026Article
- From imaging to omics: deep learning is bridging MRI and liquid biopsy in bone tumor diagnosis.Journal of bone oncology · 2026Review
- Survival prediction for bladder cancer using multimodal data with quantum neural networks and transformer architectures.Scientific reports · 2026Article
- Segmentation Methodologies for the Construction of Hyperspectral Cell Nuclei Databases in Histopathology.Bioengineering (Basel, Switzerland) · 2026Article
- Quantum-enhanced multimodal prognostic transformer for skin disease progression prediction and visualization.Scientific reports · 2026Article
- The sarcopenia artificial intelligence diagnostic decision support system (SAID DSS) - a multimodal deep learning model.BMC geriatrics · 2026Article
- A Sensor-Oriented Multimodal Medical Data Acquisition and Modeling Framework for Tumor Grading and Treatment Response Analysis.Sensors (Basel, Switzerland) · 2026Article
- Review
- AI-driven radiogenomics in gynecologic oncology: from radiological digital biopsy to a new paradigm in precision therapy.Frontiers in oncology · 2026Review
- AI in Cancer Prognosis: A Systematic Review of Multimodal Models Combining Pathology Images and High-Throughput Omics.Cancer informatics · 2026Article
- Multimodal artificial intelligence and machine learning in oncology: from data integration to precision cancer care.Frontiers in digital health · 2026Review
- Deep learning in the early diagnosis of acute aortic dissection.Frontiers in cardiovascular medicine · 2026Review
2 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
The rapid development of diagnostic technologies in healthcare is leading to higher requirements for physicians to handle and integrate the heterogeneous, yet complementary data that are produced during routine practice. For instance, the personalized diagnosis and treatment planning for a single cancer patient relies on various images (e.g. radiology, pathology and camera images) and non-image data (e.g. clinical data and genomic data). However, such decision-making procedures can be subjective, qualitative, and have large inter-subject variabilities. With the recent advances in multimodal deep learning technologies, an increasingly large number of efforts have been devoted to a key question: how do we extract and aggregate multimodal information to ultimately provide more objective, quantitative computer-aided clinical decision making? This paper reviews the recent studies on dealing with such a question. Briefly, this review will include the (a) overview of current multimodal learning workflows, (b) summarization of multimodal fusion methods, (c) discussion of the performance, (d) applications in disease diagnosis and prognosis, and (e) challenges and future directions.
Indexed as
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.