BACKGROUND
With the accumulation of electronic health records data and the development of artificial intelligence, patients with cancer urgently need new evidence of more personalized clinical and demographic characteristics and more sophisticated treatment and prevention strategies. However, no research has systematically analyzed the application and significance of electronic health records and artificial intelligence in cancer care.
OBJECTIVE
In this study, we reviewed the literature on the application of AI based on EHR data from patients with cancer, hoping to provide reference for subsequent researchers, and help accelerate the application of EHR data and AI technology in the field of cancer, so as to help patients get more scientific and accurate treatment.
METHODS
Three databases were systematically searched to retrieve potentially relevant articles published from January 2009 to October 2020. A combination of terms related to "electronic health records", "artificial intelligence" and "cancer" was used to search for these publications.
RESULTS
Of the 1034 articles considered, 148 met the inclusion criteria. The review has shown that ensemble methods and deep learning were on the rise. It presented the representative literatures on the subfield of cancer diagnosis, treatment and care. In addition, the vast majority of studies in this area were based on private institutional databases, resulting in poor portability of the proposed methodology process.
CONCLUSIONS
The use of new methods and electronic health records data sharing and fusion were recommended for future research. With the help of specialists, artificial intelligence and the mining of massive electronic medical records could provide great opportunities for improving cancer management.
A Multi-Center Study of COVID-19 Patient Prognosis Using Deep Learning-based CT Image Analysis and Electronic Health Records
