Summary of Improving the Quality Of Persian Clinical Text with a Novel Spelling Correction System, by Seyed Mohammad Sadegh Dashti et al.
Improving the quality of Persian clinical text with a novel spelling correction system
by Seyed Mohammad Sadegh Dashti, Seyedeh Fatemeh Dashti
First submitted to arxiv on: 7 Aug 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 paper proposes a novel approach to detect and correct spelling errors in Persian clinical text, which is crucial for accurate Electronic Health Records (EHRs). The researchers tackle the challenge of real-word error correction in Persian, which has abundant vocabulary and complex characteristics. By developing an innovative method, the authors aim to improve the accuracy of spelling in EHRs, ensuring efficient clinical care, research, and patient safety. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper tries to fix a big problem with medical records written in Persian. It’s hard to spell-check these records because Persian has many words and is tricky to understand. The researchers are working on a new way to find and correct spelling mistakes. This will make it easier for doctors and researchers to use the records, which is important for patient safety. |
