Data Sets were generated using the Weakly Supervised NER pipeline (https://github.com/HUMADEX/Weekly-Supervised-NER-pipline) to train the symptom extraction NER models. 

Supported Languages and dataset locations for the specific language:

    English (base language): https://huggingface.co/HUMADEX/english_medical_ner
    German: https://huggingface.co/HUMADEX/german_medical_ner
    Italian: https://huggingface.co/HUMADEX/italian_medical_ner
    Spanish: https://huggingface.co/HUMADEX/spanish_medical_ner
    Greek: https://huggingface.co/HUMADEX/german_medical_ner
    Slovenian: https://huggingface.co/HUMADEX/slovenian_medical_ner
    Polish: https://huggingface.co/HUMADEX/polish_medical_ner
    Portuguese: https://huggingface.co/HUMADEX/portugese_medical_ner

Dataset Building 

• Data Integration and Preprocessing
• Data Cleaning
• Annotation with Stanza's i2b2 Clinical Model 
• Translation into the targeted language
• Word Alignment 
• Data Augmentation 

Acknowledgement
This dataset 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.

Authors:
dr. Izidor Mlakar, Rigona Sallauka, dr. Umut Arioz, dr. Matej Rojc

Please cite as:

Article title: Weakly-Supervised Multilingual Medical NER For Symptom Extraction For Low-Resource Languages
Doi: 10.20944/preprints202504.1356.v1
Website: https://www.preprints.org/manuscript/202504.1356/v1