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# English Medical NER
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## Use
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- **Primary Use Case**: This model is designed to extract medical entities such as symptoms, diagnostic tests, and treatments from clinical text in the English language.
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- **Applications**: Suitable for healthcare professionals, clinical data analysis, and research into medical text processing.
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# English Medical NER
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## Acknowledgement
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This model had been created as part of joint research of HUMADEX research group (https://www.linkedin.com/company/101563689/) and has received funding by the European Union Horizon Europe Research and Innovation Program project SMILE (grant number 101080923) and Marie Skłodowska-Curie Actions (MSCA) Doctoral Networks, project BosomShield ((rant number 101073222). Responsibility for the information and views expressed herein lies entirely with the authors.
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Authors:
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dr. Izidor Mlakar, Rigon Sallauka, dr. Umut Arioz, dr. Matej Rojc
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## Use
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- **Primary Use Case**: This model is designed to extract medical entities such as symptoms, diagnostic tests, and treatments from clinical text in the English language.
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- **Applications**: Suitable for healthcare professionals, clinical data analysis, and research into medical text processing.
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