학술논문
Integrating Multi-omics Data with EHR for Precision Medicine Using Advanced Artificial Intelligence
Document Type
Periodical
Author
Source
IEEE Reviews in Biomedical Engineering IEEE Rev. Biomed. Eng. Biomedical Engineering, IEEE Reviews in. PP(99):1-15
Subject
Language
ISSN
1937-3333
1941-1189
1941-1189
Abstract
With the recent advancement of novel biomedical technologies such as high-throughput sequencing and wearable devices, multi-modal biomedical data ranging from multi-omics molecular data to real-time continuous bio-signals are generated at an unprecedented speed and scale every day. For the first time, these multi-modal biomedical data are able to make precision medicine close to reality. However, due to data volume and complexity, making good use of these multi-modal biomedical data requires major effort. Researchers and clinicians are actively developing artificial intelligence (AI) approaches for data-driven knowledge discovery and causal inference using a variety of biomedical data modalities. These AI-based approaches have demonstrated promising results in various biomedical and healthcare applications. In this review paper, we summarize the state-of-the-art AI models for integrating multi-omics data and electronic health records (EHRs) for precision medicine. We discuss the challenges and opportunities in integrating multi-omics data with EHRs and future directions. We hope this review can inspire future research and development in integrating multi-omics data with EHRs for precision medicine.