RadioLOGIC, a healthcare model for processing electronic health records and decision-making in breast disease
Published in Cell Reports Medicine, 2023
Recommended citation: Zhang, T., Tan, T., Wang, X. et al. (2023). "RadioLOGIC, a healthcare model for processing electronic health records and decision-making in breast disease." Cell Reports Medicine. 4(8). https://doi.org/10.1016/j.xcrm.2023.101131
Digital health data used in diagnostics, patient care, and oncology research continue to accumulate exponentially. Most medical information, and particularly radiology results, are stored in free-text format, and the potential of these data remains untapped. In this study, a radiological repomics-driven model incorporating medical token cognition (RadioLOGIC) is proposed to extract repomics (report omics) features from unstructured electronic health records and to assess human health and predict pathological outcome via transfer learning.
Recommended citation: Zhang, T., Tan, T., Wang, X. et al. (2023). “RadioLOGIC, a healthcare model for processing electronic health records and decision-making in breast disease.” Cell Reports Medicine. 4(8).