Multimodal biomedical AI
Yale University · Harvard University · +1 more institution
Abstract
The increasing availability of biomedical data from large biobanks, electronic health records, medical imaging, wearable and ambient biosensors, and the lower cost of genome and microbiome sequencing have set the stage for the development of multimodal artificial intelligence solutions that capture the complexity of human health and disease. In this Review, we outline the key applications enabled, along with the technical and analytical challenges. We explore opportunities in personalized medicine, digital clinical trials, remote monitoring and care, pandemic surveillance, digital twin technology and virtual health assistants. Further, we survey the data, modeling and privacy challenges that must be overcome…
Citation impact
- FWCI
- 55.21
- Percentile
- 100%
- References
- 180
Authors
4Topics & keywords
- Computer science
- Digital health
- Biobank
- Data science
- Wearable computer
- Wearable technology
- Precision medicine
- Applications of artificial intelligence
- Good health and well-being