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• W4308885870 abstract "Machine learning is frequently being leveraged to tackle problems in the health sector including utilization for clinical decision-support. Its use has historically been focused on single modal data. Attempts to improve prediction and mimic the multimodal nature of clinical expert decision-making has been met in the biomedical field of machine learning by fusing disparate data. This review was conducted to summarize the current studies in this field and identify topics ripe for future research. We conducted this review in accordance with the PRISMA extension for Scoping Reviews to characterize multi-modal data fusion in health. Search strings were established and used in databases: PubMed, Google Scholar, and IEEEXplore from 2011 to 2021. A final set of 128 articles were included in the analysis. The most common health areas utilizing multi-modal methods were neurology and oncology. Early fusion was the most common data merging strategy. Notably, there was an improvement in predictive performance when using data fusion. Lacking from the papers were clear clinical deployment strategies, FDA-approval, and analysis of how using multimodal approaches from diverse sub-populations may improve biases and healthcare disparities. These findings provide a summary on multimodal data fusion as applied to health diagnosis/prognosis problems. Few papers compared the outputs of a multimodal approach with a unimodal prediction. However, those that did achieved an average increase of 6.4% in predictive accuracy. Multi-modal machine learning, while more robust in its estimations over unimodal methods, has drawbacks in its scalability and the time-consuming nature of information concatenation." @default.
• W4308885870 created "2022-11-18" @default.
• W4308885870 creator A5001704304 @default.
• W4308885870 creator A5013719827 @default.
• W4308885870 creator A5031451862 @default.
• W4308885870 creator A5058023532 @default.
• W4308885870 creator A5061435169 @default.
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• W4308885870 creator A5082633688 @default.
• W4308885870 creator A5084810789 @default.
• W4308885870 date "2022-11-07" @default.
• W4308885870 modified "2023-10-10" @default.
• W4308885870 title "Multimodal machine learning in precision health: A scoping review" @default.
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