Summary of Biobridge: Unified Bio-embedding with Bridging Modality in Code-switched Emr, by Jangyeong Jeon et al.
BioBridge: Unified Bio-Embedding with Bridging Modality in Code-Switched EMR
by Jangyeong Jeon, Sangyeon Cho, Dongjoon Lee, Changhee Lee, Junyeong Kim
First submitted to arxiv on: 16 Dec 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The proposed BioBridge framework uses Natural Language Processing (NLP) to analyze Electronic Medical Records (EMRs) in written free-text form, enhancing decision-making in Pediatric Emergency Departments (PEDs). This novel approach is particularly useful for non-English speaking countries where EMR data often contains code-switched English words with clinical significance. The BioBridge framework consists of two modules: “bridging modality in context” and “unified bio-embedding.” Experimental results demonstrate the proposed BioBridge significantly outperforms traditional machine learning models on metrics such as F1 score, AUROC, AUPRC, and Brier score. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper introduces a new way to help doctors make better decisions when treating children in emergency rooms. It uses special computer programs to understand medical records that are written in different languages. This is important because many countries don’t speak English as their main language, but they still use some English words in their medical records. The program has two parts: one helps understand the medical records better, and the other connects the medical knowledge with general language understanding. The results show that this new approach works much better than previous methods. |
Keywords
» Artificial intelligence » Embedding » F1 score » Language understanding » Machine learning » Natural language processing » Nlp
