Multimodal machine learning in precision health: A scoping review
Northwestern University · Cornell University · +4 more institutions
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…
Citation impact
- FWCI
- 94.42
- Percentile
- 100%
- References
- 202
Authors
9Topics & keywords
- Computer science
- Artificial intelligence
- Machine learning
- Multimodal therapy
- Psychology
- Psychotherapist