ArticleAn international journal on information fusion2022
Data harmonisation for information fusion in digital healthcare: A state-of-the-art systematic review, meta-analysis and future research directions.
Article in An international journal on information fusion, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.
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Who cites it
46 citing papers in PubMed.
- Growth Hormone Treatment Response and Machine Learning-Based Prediction in Idiopathic GHD and ISS: Analysis of the Korean LG Growth Study.Clinical endocrinology · 2026Observational
- Statistical methods for retrospective harmonization of longitudinal epidemiological data: a scoping review.European journal of epidemiology · 2026Article
- Development and evaluation of wrist- and thigh-worn accelerometer algorithms using self-training machine learning models for classification of activity type and posture: towards device placement-agnostic methods in the ProPASS consortium.The international journal of behavioral nutrition and physical activity · 2026Article
- [A bidirectional feature mapping classification model based on multi-constrained latent representation learning for differential diagnosis of pneumonia].Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2026Article
- Multimodal Information Fusion for Control of Rehabilitation Robots in Motor Dysfunction: A Review.Bioengineering (Basel, Switzerland) · 2026Review
- Decoding the Glioblastoma Microenvironment: AI-Driven Analysis of Cellular MRI Signatures for Targeted Therapy.Cellular and molecular neurobiology · 2026Review
- Computational approaches to multimodal data integration in rheumatoid arthritis: from data landscape to clinical translation.Briefings in bioinformatics · 2026Review
- Big Data Analytics Framework for Early Breast Cancer Detection Using Optimized MapReduce and Deep Learning on Large-Scale Mammographic Data.International journal of biomedical imaging · 2026Article
- Ontology- and LLM-based data harmonization for federated learning in healthcare.Frontiers in digital health · 2026Article
- A Systematic Literature Review on Integrated Deep Learning and Multiagent Vision-Language Frameworks for Pathology Image Analysis and Report Generation.Computational and structural biotechnology journal · 2026Review
- Evolving non-invasive biomarkers in NSCLC immunotherapy: integrating liquid biopsy and multi-omics profiling for precision oncology.Frontiers in immunology · 2026Review
- mpMRI-based MGMT methylation status prediction for glioblastoma through off-the-shelf deep features: A multi-dataset feasibility study.Journal of applied clinical medical physics · 2025Article
- Reply: SABRE for airway quantification in idiopathic pulmonary fibrosis: clarifications, limitations, and next steps.The European respiratory journal · 2025Article
- Fibrotic and vascular abnormalities quantified by an AI-based model are associated with outcomes in patients with idiopathic pulmonary fibrosis.BMC pulmonary medicine · 2025Article
- A Multi-Dimensional Framework for Data Quality Assurance in Cancer Imaging Repositories.Cancers · 2025Article
- Artificial intelligence in drug development for delirium and Alzheimer's disease.Acta pharmaceutica Sinica. B · 2025Review
- Developing a reliable predictive model for the biodegradability index in industrial complex effluent.Scientific reports · 2025Article
- Uncertainties in outcome modelling in radiation oncology.Physics and imaging in radiation oncology · 2025Review
- A comparative analysis of image harmonization techniques in mitigating differences in CT acquisition and reconstruction.Physics in medicine and biology · 2025Article
- FUTURE-AI: international consensus guideline for trustworthy and deployable artificial intelligence in healthcare.BMJ (Clinical research ed.) · 2025Article
Corrections and comments
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Authors and funding
26 authors.
Funding
Abstract
Removing the bias and variance of multicentre data has always been a challenge in large scale digital healthcare studies, which requires the ability to integrate clinical features extracted from data acquired by different scanners and protocols to improve stability and robustness. Previous studies have described various computational approaches to fuse single modality multicentre datasets. However, these surveys rarely focused on evaluation metrics and lacked a checklist for computational data harmonisation studies. In this systematic review, we summarise the computational data harmonisation approaches for multi-modality data in the digital healthcare field, including harmonisation strategies and evaluation metrics based on different theories. In addition, a comprehensive checklist that summarises common practices for data harmonisation studies is proposed to guide researchers to report their research findings more effectively. Last but not least, flowcharts presenting possible ways for methodology and metric selection are proposed and the limitations of different methods have been surveyed for future research.
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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.