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Macbert Base Chinese Medical Collation

Developed by 9pinus
A medical text spell-checking model fine-tuned on macbert, trained on a 300-million-scale medical dataset with 96% accuracy
Downloads 23
Release Time : 3/2/2022

Model Overview

A spell-checking model specifically designed for medical scenarios, capable of detecting and correcting spelling errors in medical texts

Model Features

Medical Domain Optimization
Fine-tuned on a 300-million-scale medical dataset, optimized for medical terminology and expressions
Noise Simulation Training
Enhanced error correction capability by adding 30% visual/phonetic similar character noise
High Accuracy
Achieves 96% accuracy on test datasets

Model Capabilities

Medical Text Spell Checking
Misspelling Identification
Similar Character Correction

Use Cases

Medical Document Processing
Electronic Medical Record Proofreading
Automatically detects spelling errors in drug names and medical terms in medical records
Accurately identifies common errors such as 'ᔞ肖唑' should be 'į”˛įĄå”‘'
Medical Paper Proofreading
Checks spelling of professional terms in academic papers
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